Metabolic trajectories of diabetic ketoacidosis onset described by breath analysis.

Purpose: This feasibility study aimed to investigate the use of exhaled breath analysis to capture and quantify relative changes of metabolites during resolution of acute diabetic ketoacidosis under insulin and rehydration therapy. Methods: Breath analysis was conducted on 30 patients of which 5 with DKA. They inflated Nalophan bags, and their metabolic content was subsequently interrogated by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). Results: SESI-HRMS analysis showed that acetone, pyruvate, and acetoacetate, which are well known to be altered in DKA, were readily detectable in breath of participants with DKA. In addition, a total of 665 mass spectral features were found to significantly correlate with base excess and prompt metabolic trajectories toward an in-control state as they progress toward homeostasis. Conclusion: This study provides proof-of-principle for using exhaled breath analysis in a real ICU setting for DKA monitoring. This non-invasive new technology provides new insights and a more comprehensive overview of the effect of insulin and rehydration during DKA treatment.

Low Levels of HIV Stigma Among Transgender Women Receiving HIV Care.

Despite the prevalence of HIV among transgender women (TGW), gaps exist in understanding the impact of HIV-related stigma (HRS) on TGW with HIV. This is a small cross-sectional pilot study examining HRS in TGW (n=18) with HIV in Miami, FL, who completed a survey during an HIV clinical visit. In contrast with previous studies, results demonstrated low levels of HRS and suggest the potential of increasing acceptance of TGW with HIV as a contributing factor. Larger studies are needed to explore factors underlying HRS with the aim of further reducing stigma among TGW with HIV.

Breaking Barriers: A Single-Center Real-World Experience With Recruitment and Administration of COVID-19 Monoclonal Antibodies and Opportunities for Improvement.

We conducted a retrospective exploratory study evaluating factors associated with selection to receive and infusion with coronavirus disease 2019 monoclonal antibodies. While priority was given to high-risk patients, patients with increased Social Vulnerability Index scores were less likely to present for infusion, raising concern that social factors created barriers to treatment.

Challenges to Using Big Data in Cancer.

Big data in healthcare can enable unprecedented understanding of diseases and their treatment, particularly in oncology. These data may include electronic health records, medical imaging, genomic sequencing, payor records, and data from pharmaceutical research, wearables, and medical devices. The ability to combine datasets and use data across many analyses is critical to the successful use of big data and is a concern for those who generate and use the data. Interoperability and data quality continue to be major challenges when working with different healthcare datasets. Mapping terminology across datasets, missing and incorrect data, and varying data structures make combining data an onerous and largely manual undertaking. Data privacy is another concern addressed by the Health Insurance Portability and Accountability Act, the Common Rule, and the General Data Protection Regulation. The use of big data is now included in the planning and activities of the FDA and the European Medicines Agency. The willingness of organizations to share data in a precompetitive fashion, agreements on data quality standards, and institution of universal and practical tenets on data privacy will be crucial to fully realizing the potential for big data in medicine.

Case Studies for Overcoming Challenges in Using Big Data in Cancer.

The analysis of big healthcare data has enormous potential as a tool for advancing oncology drug development and patient treatment, particularly in the context of precision medicine. However, there are challenges in organizing, sharing, integrating, and making these data readily accessible to the research community. This review presents five case studies illustrating various successful approaches to addressing such challenges. These efforts are CancerLinQ, the American Association for Cancer Research Project GENIE, Project Data Sphere, the National Cancer Institute Genomic Data Commons, and the Veterans Health Administration Clinical Data Initiative. Critical factors in the development of these systems include attention to the use of robust pipelines for data aggregation, common data models, data deidentification to enable multiple uses, integration of data collection into physician workflows, terminology standardization and attention to interoperability, extensive quality assurance and quality control activity, incorporation of multiple data types, and understanding how data resources can be best applied. By describing some of the emerging resources, we hope to inspire consideration of the secondary use of such data at the earliest possible step to ensure the proper sharing of data in order to generate insights that advance the understanding and the treatment of cancer.

Encoding laboratory testing data: case studies of the national implementation of HHS requirements and related standards in five laboratories.

OBJECTIVE: Assess the effectiveness of providing Logical Observation Identifiers Names and Codes (LOINC®)-to-In Vitro Diagnostic (LIVD) coding specification, required by the United States Department of Health and Human Services for SARS-CoV-2 reporting, in medical center laboratories and utilize findings to inform future United States Food and Drug Administration policy on the use of real-world evidence in regulatory decisions. MATERIALS AND METHODS: We compared gaps and similarities between diagnostic test manufacturers' recommended LOINC® codes and the LOINC® codes used in medical center laboratories for the same tests. RESULTS: Five medical centers and three test manufacturers extracted data from laboratory information systems (LIS) for prioritized tests of interest. The data submission ranged from 74 to 532 LOINC® codes per site. Three test manufacturers submitted 15 LIVD catalogs representing 26 distinct devices, 6956 tests, and 686 LOINC® codes. We identified mismatches in how medical centers use LOINC® to encode laboratory tests compared to how test manufacturers encode the same laboratory tests. Of 331 tests available in the LIVD files, 136 (41%) were represented by a mismatched LOINC® code by the medical centers (chi-square 45.0, 4 df, P < .0001). DISCUSSION: The five medical centers and three test manufacturers vary in how they organize, categorize, and store LIS catalog information. This variation impacts data quality and interoperability. CONCLUSION: The results of the study indicate that providing the LIVD mappings was not sufficient to support laboratory data interoperability. National implementation of LIVD and further efforts to promote laboratory interoperability will require a more comprehensive effort and continuing evaluation and quality control.

Evaluation of enhanced darkfield microscopy and hyperspectral imaging for rapid screening of TiO2 and SiO2 nanoscale particles captured on filter media.

Here we report on initial efforts to evaluate enhanced darkfield microscopy (EDFM) and light scattering Vis-NIR hyperspectral imaging (HSI) as a rapid screening tool for the offline analysis of mixed cellulose ester (MCE) filter media used to collect airborne nanoparticulate from work environments. For this study, the materials of interest were nanoscale titanium dioxide (TiO2 ) and silicon dioxide (SiO2 ; silica), chosen for their frequent use in consumer products. TiO2 and SiO2 nanoscale particles (NPs) were collected on MCE filter media and were imaged and analyzed via EDFM-HSI. When visualized by EDFM, TiO2 and SiO2 NPs were readily apparent as bright spherical structures against a dark background. Moreover, TiO2 and SiO2 NPs were identified in hyperspectral images. EDFM-HSI images and data were compared to scanning transmission electron microscopy (STEM), a NIST-traceable technique for particle size analysis, and the current gold standard for offline analysis of filter media. As expected, STEM provided more accurate sizing and morphology data when compared to EDFM-HSI, but is not ideal for rapid screening of the presence of NPs of interest since it is a costly, low-throughput technique. In this study, we demonstrate the utility of EDFM-HSI in rapidly visualizing and identifying TiO2 and SiO2 NPs on MCE filters. This screening method may prove useful in expediting time-to-knowledge compared to electron microscopy. Future work will expand this evaluation to other industrially relevant NPs, other filter media types, and real-world filter samples from occupational exposure assessments.

Evaluation of classification methods for identifying multiwalled carbon nanotubes collected on mixed cellulose ester filter media.

Enhanced darkfield microscopy (EDFM) and hyperspectral imaging (HSI) are being evaluated as a potential rapid screening modality to reduce the time-to-knowledge for direct visualisation and analysis of filter media used to sample nanoparticulate from work environments, as compared to the current analytical gold standard of transmission electron microscopy (TEM). Here, we compare accuracy, specificity, and sensitivity of several hyperspectral classification models and data preprocessing techniques to determine how to most effectively identify multiwalled carbon nanotubes (MWCNTs) in hyperspectral images. Several classification schemes were identified that are capable of classifying pixels as MWCNT(+) or MWCNT(-) in hyperspectral images with specificity and sensitivity over 99% on the test dataset. Functional principal component analysis (FPCA) was identified as an appropriate data preprocessing technique, testing optimally when coupled with a quadratic discriminant analysis (QDA) model with forward stepwise variable selection and with a support vector machines (SVM) model. The success of these methods suggests that EDFM-HSI may be reliably employed to assess filter media exposed to MWCNTs. Future work will evaluate the ability of EDFM-HSI to quantify MWCNTs collected on filter media using this classification algorithm framework using the best-performing model identified here - quadratic discriminant analysis with forward stepwise selection on functional principal component data - on an expanded sample set.

Nanotechnology Fundamentals Applied to Clinical Infectious Diseases and Public Health.

Nanotechnology involves the discovery and fabrication of nanoscale materials possessing unique physicochemical properties that are being employed in industry and medicine. Infectious Diseases clinicians and public health scientists utilize nanotechnology applications to diagnose, treat, and prevent infectious diseases. However, fundamental principles of nanotechnology are often presented in technical formats that presuppose an advanced knowledge of chemistry, physics, and engineering, thereby limiting the clinician's grasp of the underlying science. While nanoscience is technically complex, it need not be out of reach of the clinical practitioner. The aim of this review is to introduce fundamental principles of nanotechnology in an accessible format, describe examples of current clinical infectious diseases and public health applications, and provide a foundation that will aid understanding of and appreciation for this burgeoning and important field of science.

Applying concurrent multidisciplinary care to gender affirmation in transgender women: A case series.

Gender affirmation surgeries, though important for many transgender persons, can be numerous. Combining surgeries, as presented in this case series, affords many benefits to patients without increasing risk or complications.

Sample preparation method for visualization of nanoparticulate captured on mixed cellulose ester filter media by enhanced darkfield microscopy and hyperspectral imaging.

A significant hurdle in conducting effective health and safety hazard analysis and risk assessment for the nanotechnology workforce is the lack of a rapid method for the direct visualization and analysis of filter media used to sample nanomaterials from work environments that represent potential worker exposure. Current best-known methods include transmission electron microscopy (TEM) coupled with energy dispersive x-ray spectroscopy (EDS) for elemental identification. TEM-EDS is considerably time-, cost-, and resource-intensive, which may prevent timely health and safety recommendations and corrective actions. A rapid screening method is currently being explored using enhanced darkfield microscopy with hyperspectral imaging (EDFM-HSI). For this approach to be effective, rapid, and easy, sample preparation that is amenable to the analytical technique is needed. Here, we compare the sample preparation steps for mixed cellulose ester (MCE) filter media specified in NIOSH Method 7400-Asbestos and Other Fibers by Phase Contrast Microscopy (PCM)-against a new method, which involves saturation of the filter media with acetone. NIOSH Method 7400 was chosen as a starting point since it is an established technique for preparing transparent MCE filters for optical microscopy. Limitations in this method led to the development and comparison of a new method. The new method was faster, easier, and rendered filters more transparent, resulting in improved visualization and analysis of nanomaterials via EDFM-HSI. This new method is suitable for a rapid screening protocol due to its speed, ease of use, and the improvement in image acquisition and analysis.

Petrochemical Wastewater and Produced Water.

Petrochemical and oil & gas industries are crucial for global economy while great attention is needed for the related contamination and its impact on the environment. Papers reviewed herein represent the recent research and development on petrochemical wastewater and produced water from oil & gas industry, published in 2017 and beginning of 2018 globally. In the petrochemical wastewater, progresses were made in characterization, physicochemical treatment and biological treatment. In the oil & gas produced water, efforts were made on the characterization, the environmental impact and treatment options.

Two key cathepsins, TgCPB and TgCPL, are targeted by the vinyl sulfone inhibitor K11777 in in vitro and in vivo models of toxoplasmosis.

Although toxoplasmosis is one of the most common parasitic infections worldwide, therapeutic options remain limited. Cathepsins, proteases that play key roles in the pathogenesis of toxoplasmosis and many other protozoan infections, are important potential therapeutic targets. Because both TgCPB and TgCPL play a role in T. gondii invasion, we evaluated the efficacy of the potent, irreversible vinyl sulfone inhibitor, K11777 (N-methyl-piperazine-Phe-homoPhe-vinylsulfone-phenyl). The inhibitor's toxicity and pharmacokinetic profile have been well-studied because of its in vitro and in vivo activity against a number of parasites. We found that it inhibited both TgCPB (EC50 = 114 nM) and TgCPL (EC50 = 71 nM) in vitro. K11777 also inhibited invasion of human fibroblasts by RH tachyzoites by 71% (p = 0.003) and intracellular replication by >99% (p<0.0001). In vivo, a single dose of K11777 led to 100% survival of chicken embryos in an model of acute toxoplasmosis (p = 0.015 Cox regression analysis). Therefore, K11777 shows promise as a novel therapeutic agent in the treatment of toxoplasmosis, and may prove to be a broadly effective anti-parasitic agent.

Hyperspectral data influenced by sample matrix: the importance of building relevant reference spectral libraries to map materials of interest.

Hyperspectral imaging (HSI) and mapping are increasingly used for visualization and identification of nanoparticles (NPs) in a variety of matrices, including aqueous suspensions and biological samples. Reference spectral libraries (RSLs) contain hyperspectral data collected from materials of known composition and are used to detect the known materials in experimental samples through a one-to-one pixel "mapping" process. In some HSI studies, RSLs created from raw NPs were used to map NPs in experimental samples in a different matrix; for example, RSLs created from NPs in suspension to map NPs in biological tissue. Others have utilized RSLs created from NPs in the same matrix. However, few studies have systematically compared hyperspectral data as a function of the matrix in which the NPs are found and its impact on mapping results. The objective of this study is to compare RSLs created from metal oxide NPs in aqueous suspensions to RSLs created from the same NPs in rat tissues following in vivo inhalation exposure, and to investigate the differences in mapping that result from the use of each RSL. Results demonstrate that the spectral profiles of these NPs are matrix dependent: RSLs created from NPs in positive control tissues mapped to experimental tissues more appropriately than RSLs created from NPs in suspension. Aqueous suspension RSLs mapped 0-602 out of 500,424 pixels per tissue image while tissue RSLs mapped 689-18,435 pixels for the same images. This study underscores the need for appropriate positive controls for the creation of RSLs for mapping NPs in experimental samples.

Biodistribution of inhaled metal oxide nanoparticles mimicking occupational exposure: a preliminary investigation using enhanced darkfield microscopy.

Inhalation exposure to engineered nanomaterials (ENMs) may result in adverse pulmonary and/or systemic health effects. In this study, enhanced darkfield microscopy (EDFM) was used as a novel approach to visualizing industrial metal oxide nanoparticles (NPs) (silica, ceria, or alumina) in multiple tissue types following inhalation in rats mimicking occupational exposures. Advantages of EDFM over electron microscopy (EM) include reduced cost, time, and ease of sample preparation and operation. Following 4-6 hour inhalation exposures at three concentrations (3.5-34.0 mg/m3 ), lungs and secondary organs were harvested at 24 hours or 7 days post-exposure and prepared for brightfield (BF) microscopy and EDFM. NPs were visualized within the lung and associated lymphatic tissues and in major organs of excretion (liver, spleen, kidney). EDFM also revealed NPs within pulmonary blood vessels and localization within specific regions of toxicological relevance in liver and kidney, indicating pathways of excretion. Results demonstrate the utility of EDFM for rapid direct visualization of NPs in various tissue types and suggest the potential for metal oxide NPs to distribute to secondary tissues following inhalation exposure. Confirmation of the composition, distribution, and relative abundance of inhaled NPs will be pursued by combining EDFM with hyperspectral imaging (HSI) and mapping.

Occupational exposure to airborne nanomaterials: An assessment of worker exposure to aerosolized metal oxide nanoparticles in a semiconductor fab and subfab.

This occupational exposure assessment study characterized potential inhalation exposures of workers to engineered nanomaterials associated with chemical mechanical planarization wafer polishing processes in a semiconductor research and development facility. Air sampling methodology was designed to capture airborne metal oxide nanoparticles for characterization. The research team obtained air samples in the fab and subfab areas using a combination of filter-based capture methods to determine particle morphology and elemental composition and real-time direct-reading instruments to determine airborne particle counts. Filter-based samples were analyzed by electron microscopy and energy-dispersive x-ray spectroscopy while real-time particle counting data underwent statistical analysis. Sampling was conducted during worker tasks associated with preventive maintenance and quality control that were identified as having medium to high potential for inhalation exposure based on qualitative assessments. For each sampling event, data was collected for comparison between the background, task area, and personal breathing zone. Sampling conducted over nine months included five discrete sampling series events in coordination with on-site employees under real working conditions. The number of filter-based samples captured was: eight from worker personal breathing zones; seven from task areas; and five from backgrounds. A complementary suite of direct-reading instruments collected data for seven sample collection periods in the task area and six in the background. Engineered nanomaterials of interest (Si, Al, Ce) were identified in filter-based samples from all areas of collection, existing as agglomerates (>500 nm) and nanoparticles (100-500 nm). Particle counts showed an increase in number concentration above background during a subset of the job tasks, but particle counts in the task areas were otherwise not significantly higher than background. Additional data is needed to support further statistical analysis and determine trends; however, this initial investigation suggests that nanoparticles used or generated by the wafer polishing process become aerosolized and may be accessible for inhalation exposures by workers performing tasks in the subfab and fab. Additional research is needed to further quantify the degree of exposure and link these findings to related hazard research.

NIOSH field studies team assessment: Worker exposure to aerosolized metal oxide nanoparticles in a semiconductor fabrication facility.

The ubiquitous use of engineered nanomaterials-particulate materials measuring approximately 1-100 nanometers (nm) on their smallest axis, intentionally engineered to express novel properties-in semiconductor fabrication poses unique issues for protecting worker health and safety. Use of new substances or substances in a new form may present hazards that have yet to be characterized for their acute or chronic health effects. Uncharacterized or emerging occupational health hazards may exist when there is insufficient validated hazard data available to make a decision on potential hazard and risk to exposed workers under condition of use. To advance the knowledge of potential worker exposure to engineered nanomaterials, the National Institute for Occupational Safety and Health Nanotechnology Field Studies Team conducted an on-site field evaluation in collaboration with on-site researchers at a semiconductor research and development facility on April 18-21, 2011. The Nanomaterial Exposure Assessment Technique (2.0) was used to perform a complete exposure assessment. A combination of filter-based sampling and direct-reading instruments was used to identify, characterize, and quantify the potential for worker inhalation exposure to airborne alumina and amorphous silica nanoparticles associated with th e chemical mechanical planarization wafer polishing process. Engineering controls and work practices were evaluated to characterize tasks that might contribute to potential exposures and to assess existing engineering controls. Metal oxide structures were identified in all sampling areas, as individual nanoparticles and agglomerates ranging in size from 60 nm to >1,000 nm, with varying structure morphology, from long and narrow to compact. Filter-based samples indicated very little aerosolized material in task areas or worker breathing zone. Direct-reading instrument data indicated increased particle counts relative to background in the wastewater treatment area; however, particle counts were very low overall, indicating a well-controlled working environment. Recommendations for employees handling or potentially exposed to engineered nanomaterials include hazard communication, standard operating procedures, conservative ventilation systems, and prevention through design in locations where engineered nanomaterials are used or stored, and routine air sampling for occupational exposure assessment and analysis.

Hyperspectral imaging of nanoparticles in biological samples: Simultaneous visualization and elemental identification.

While engineered nanomaterials (ENMs) are increasingly incorporated into industrial processes and consumer products, the potential biological effects and health outcomes of exposure remain unknown. Novel advanced direct visualization techniques that require less time, cost, and resource investment than electron microscopy (EM) are needed for identifying and locating ENMs in biological samples. Hyperspectral imaging (HSI) combines spectrophotometry and imaging, using advanced optics and algorithms to capture a spectrum from 400 to 1000 nm at each pixel in an enhanced dark-field microscopic (EDFM) image. HSI-EDFM can be used to confirm the identity of the materials of interest in a sample and generate an image "mapping" their presence and location in a sample. Hyperspectral mapping is particularly important for biological samples, where ENM morphology is visually indistinct from surrounding tissue structures. While use of HSI (without mapping) is increasing, no studies to date have compared results from hyperspectral mapping with conventional methods. Thus, the objective of this study was to utilize EDFM-HSI to locate, identify, and map metal oxide ENMs in ex vivo histological porcine skin tissues, a toxicological model of cutaneous exposure, and compare findings with those of Raman spectroscopy (RS), energy-dispersive X-ray spectroscopy (EDS), and scanning electron microscopy (SEM). Results demonstrate that EDFM-HSI mapping is capable of locating and identifying ENMs in tissue, as confirmed by conventional methods. This study serves as initial confirmation of EDFM-HSI mapping as a novel and higher throughput technique for ENM identification in biological samples, and serves as the basis for further protocol development utilizing EDFM-HSI for semiquantitation of ENMs.

Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping.

Nanomaterials are increasingly prevalent throughout industry, manufacturing, and biomedical research. The need for tools and techniques that aid in the identification, localization, and characterization of nanoscale materials in biological samples is on the rise. Currently available methods, such as electron microscopy, tend to be resource-intensive, making their use prohibitive for much of the research community. Enhanced darkfield microscopy complemented with a hyperspectral imaging system may provide a solution to this bottleneck by enabling rapid and less expensive characterization of nanoparticles in histological samples. This method allows for high-contrast nanoscale imaging as well as nanomaterial identification. For this technique, histological tissue samples are prepared as they would be for light-based microscopy. First, positive control samples are analyzed to generate the reference spectra that will enable the detection of a material of interest in the sample. Negative controls without the material of interest are also analyzed in order to improve specificity (reduce false positives). Samples can then be imaged and analyzed using methods and software for hyperspectral microscopy or matched against these reference spectra in order to provide maps of the location of materials of interest in a sample. The technique is particularly well-suited for materials with highly unique reflectance spectra, such as noble metals, but is also applicable to other materials, such as semi-metallic oxides. This technique provides information that is difficult to acquire from histological samples without the use of electron microscopy techniques, which may provide higher sensitivity and resolution, but are vastly more resource-intensive and time-consuming than light microscopy.

Comparative analysis of redox and inflammatory properties of pristine nanomaterials and commonly used semiconductor manufacturing nano-abrasives.

Continued expansion of the nanotechnology industry has necessitated the self-assessment of manufacturing processes, specifically in regards to understanding the health related aspects following exposure to nanomaterials. There exists a growing concern over potential occupational exposure in the semiconductor industry where Al2O3, CeO2 and SiO2 nanoparticles are commonly featured as part of the chemical mechanical planarization (CMP) process. Chronic exposure to toxicants can result not only in acute cytotoxicity but also initiation of a chronic inflammatory state associated with diverse pathologies. In the current investigation, pristine nanoparticles and CMP slurry formulations of Al2O3, SiO2 and CeO2 were employed to assess their ability to induce cytotoxicity, inflammatory responses and reactive oxygen species in a mouse alveolar macrophage cell model. The pristine nanoparticles and slurries were not intrinsically cytotoxic and did not generate free radicals but were found to act as scavengers in the presence of an oxidant stimulant. Al2O3 and SiO2 nanoparticles increased levels of pro-inflammatory cytokines while pristine SiO2 nanoparticles induced generation of F2-Isoprostanes. In co-treatment studies, the pristine nanomaterials modulated the response to the inflammatory stimulant lipopolysaccharide. The studies have established that pristine nanoparticles and slurries do not impact the cells in a similar way indicating that they should not be used as slurry substitutes in toxicity evaluations. Further, we have defined how an alveolar cell line, which would likely be the first challenged upon nanomaterial aerosolization, responds to diverse mixtures of nanomaterials. Moreover, our findings reinforce the importance of using multiple analytic methods to define the redox state of the cell following exposure to commonly used industrial nanomaterials and toxicants.