Physician marriage survey reveals sex and specialty differences in marital satisfaction factors.

Physician marriage is a valuable indicator of how vocational factors (e.g. work hours, stressors) impact satisfaction in relationships and physician wellness overall. Previous studies suggest that gender and specialty influence marriage satisfaction for physicians, though these often come from limited, local, cohorts. A cross-sectional survey was designed and distributed to publicly available email addresses representing academic and private practice physician organizations across the United States, receiving 321 responses (253 complete). Responses included data on demographics, medical specialty, age at marriage, stage of training at marriage, number of children, and factors leading to marital satisfaction/distress. A multivariable ordinal logistic regression was conducted to find associations between survey variables and marriage satisfaction. Survey results indicated that 86.5% of physicians have been married (average age at first marriage was 27.8 years old), and the rate of first marriages ending is at least 14.7%. Men had significantly more children than women. Physicians married at least once averaged 1.98 children. "Other" specialty physicians had significantly more children on average than psychiatrists. Marrying before medical school predicted practicing in private practice settings. Job stress, work hours, children, and sex were most frequently sources of marital distress, while strong communication, finances, and children were most frequently sources of marital stability. Sex differences were also found in distressing and stabilizing marital factors: Female physicians were more likely to cite their spouse's work hours and job stress as sources of marital distress. Finally, surgery specialty and Judaism were associated with higher marriage satisfaction, whereas possession of an M.D. degree was associated with lower marriage satisfaction. This study elucidated new perspectives on physician marriage and families based on specialty, practice setting, and stage of training at marriage. Future studies may focus on factors mediating specialty and sex's impact on having children and marriage satisfaction. To our knowledge, this study is the first physician marriage survey which integrates multiple factors in the analysis of physician marriages.

Spatiotemporal roles of AMPK in PARP-1- and autophagy-dependent retinal pigment epithelial cell death caused by UVA.

BACKGROUND: Although stimulating autophagy caused by UV has been widely demonstrated in skin cells to exert cell protection, it remains unknown the cellular events in UVA-treated retinal pigment epithelial (RPE) cells. METHODS: Human ARPE-19 cells were used to measure cell viability, mitochondrial reactive oxygen species (ROS), mitochondrial membrane potential (MMP), mitochondrial mass and lysosomal mass by flow cytometry. Mitochondrial oxygen consumption rate (OCR) was recorded using Seahorse XF flux analyzer. Confocal microscopic images were performed to indicate the mitochondrial dynamics, LC3 level, and AMPK translocation after UVA irradiation. RESULTS: We confirmed mitochondrial ROS production and DNA damage are two major features caused by UVA. We found the cell death is prevented by autophagy inhibitor 3-methyladenine and gene silencing of ATG5, and UVA induces ROS-dependent LC3II expression, LC3 punctate and TFEB expression, suggesting the autophagic death in the UVA-stressed RPE cells. Although PARP-1 inhibitor olaparib increases DNA damage, ROS production, and cell death, it also blocks AMPK activation caused by UVA. Interestingly we found a dramatic nuclear export of AMPK upon UVA irradiation which is blocked by N-acetylcysteine and olaparib. In addition, UVA exposure gradually decreases lysosomal mass and inhibits cathepsin B activity at late phase due to lysosomal dysfunction. Nevertheless, cathepsin B inhibitor, CA-074Me, reverses the death extent, suggesting the contribution of cathepsin B in the death pathway. When examining the role of EGFR in cellular events caused by UVA, we found that UVA can rapidly transactivate EGFR, and treatment with EGFR TKIs (gefitinib and afatinib) enhances the cell death accompanied by the increased LC3II formation, ROS production, loss of MMP and mass of mitochondria and lysosomes. Although AMPK activation by ROS-PARP-1 mediates autophagic cell death, we surprisingly found that pretreatment of cells with AMPK activators (A769662 and metformin) reverses cell death. Concomitantly, both agents block UVA-induced mitochondrial ROS production, autophagic flux, and mitochondrial fission without changing the inhibition of cathepsin B. CONCLUSION: UVA exposure rapidly induces ROS-PARP-1-AMPK-autophagic flux and late lysosomal dysfunction. Pre-inducing AMPK activation can prevent cellular events caused by UVA and provide a new protective strategy in photo-oxidative stress and photo-retinopathy.

Twelve Weeks of Intermittent Caloric Restriction Diet Mitigates Neuroinflammation in Midlife Individuals with Multiple Sclerosis: A Pilot Study with Implications for Prevention of Alzheimer's Disease.

BACKGROUND: Multiple sclerosis (MS) is a prototype neuroinflammatory disorder with increasingly recognized role for neurodegeneration. Most first-line treatments cannot prevent the progression of neurodegeneration and the resultant disability. Interventions can improve symptoms of MS and might provide insights into the underlying pathology. OBJECTIVE: To investigate the effect of intermittent caloric restriction on neuroimaging markers of MS. METHODS: We randomized ten participants with relapsing remitting MS to either a 12-week intermittent calorie restriction (iCR) diet (n = 5) or control (n = 5). Cortical thickness and volumes were measured through FreeSurfer, cortical perfusion was measured by arterial spin labeling and neuroinflammation through diffusion basis spectrum imaging. RESULTS: After 12 weeks of iCR, brain volume increased in the left superior and inferior parietal gyri (p: 0.050 and 0.049, respectively) and the banks of the superior temporal sulcus (p: 0.01). Similarly in the iCR group, cortical thickness improved in the bilateral medial orbitofrontal gyri (p: 0.04 and 0.05 in right and left, respectively), the left superior temporal gyrus (p: 0.03), and the frontal pole (p: 0.008) among others. Cerebral perfusion decreased in the bilateral fusiform gyri (p: 0.047 and 0.02 in right and left, respectively) and increased in the bilateral deep anterior white matter (p: 0.03 and 0.013 in right and left, respectively). Neuroinflammation, demonstrated through hindered and restricted water fractions (HF and RF), decreased in the left optic tract (HF p: 0.02), and the right extreme capsule (RF p: 0.007 and HF p: 0.003). CONCLUSION: These pilot data suggest therapeutic effects of iCR in improving cortical volume and thickness and mitigating neuroinflammation in midlife adults with MS.

Membrane Protein Modification Modulates Big and Small Extracellular Vesicle Biodistribution and Tumorigenic Potential in Breast Cancers In Vivo.

Extracellular vesicles (EVs) are released by cells to mediate intercellular communication under pathological and physiological conditions. While small EVs (sEVs; <100-200 nm, exosomes) are intensely investigated, the properties and functions of medium and large EVs (big EVs (bEVs); >200 nm, microvesicles) are less well explored. Here, bEVs and sEVs are identified as distinct EV populations, and it is determined that bEVs are released in a greater bEV:sEV ratio in the aggressive human triple-negative breast cancer (TNBC) subtype. PalmGRET, bioluminescence-resonance-energy-transfer (BRET)-based EV reporter, reveals dose-dependent EV biodistribution at nonlethal and physiological EV dosages, as compared to lipophilic fluorescent dyes. Remarkably, the bEVs and sEVs exhibit unique biodistribution profiles, yet individually promote in vivo tumor growth in a syngeneic immunocompetent TNBC breast tumor murine model. The bEVs and sEVs share mass-spectrometry-identified tumor-progression-associated EV surface membrane proteins (tpEVSurfMEMs), which include solute carrier family 29 member 1, Cd9, and Cd44. tpEVSurfMEM depletion attenuates EV lung organotropism, alters biodistribution, and reduces protumorigenic potential. This study identifies distinct in vivo property and function of bEVs and sEVs in breast cancer, which suggest the significant role of bEVs in diseases, diagnostic and therapeutic applications.

Diffusion histology imaging differentiates distinct pediatric brain tumor histology.

High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumors clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in their clinical management. We employed a novel Diffusion Histology Imaging (DHI) approach employing diffusion basis spectrum imaging (DBSI) derived metrics as the input classifiers for deep neural network analysis. DHI aims to detect, differentiate, and quantify heterogeneous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 85.8%. Receiver operating analysis (ROC) analysis suggested DHI's great capability in distinguishing individual tumor histology with AUC values (95% CI) of 0.984 (0.982-0.986), 0.960 (0.956-0.963), 0.991 (0.990-0.993), 0.950 (0.944-0.956), 0.977 (0.973-0.981) and 0.976 (0.972-0.979) for normal WM, densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If these results could be further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

Multiresolution Imaging Using Bioluminescence Resonance Energy Transfer Identifies Distinct Biodistribution Profiles of Extracellular Vesicles and Exomeres with Redirected Tropism.

Extracellular particles (EPs) including extracellular vesicles (EVs) and exomeres play significant roles in diseases and therapeutic applications. However, their spatiotemporal dynamics in vivo have remained largely unresolved in detail due to the lack of a suitable method. Therefore, a bioluminescence resonance energy transfer (BRET)-based reporter, PalmGRET, is created to enable pan-EP labeling ranging from exomeres (<50 nm) to small (<200 nm) and medium and large (>200 nm) EVs. PalmGRET emits robust, sustained signals and allows the visualization, tracking, and quantification of the EPs from whole animal to nanoscopic resolutions under different imaging modalities, including bioluminescence, BRET, and fluorescence. Using PalmGRET, it is shown that EPs released by lung metastatic hepatocellular carcinoma (HCC) exhibit lung tropism with varying distributions to other major organs in immunocompetent mice. It is further demonstrated that gene knockdown of lung-tropic membrane proteins, solute carrier organic anion transporter family member 2A1, alanine aminopeptidase/Cd13, and chloride intracellular channel 1 decreases HCC-EP distribution to the lungs and yields distinct biodistribution profiles. It is anticipated that EP-specific imaging, quantitative assays, and detailed in vivo characterization are a starting point for more accurate and comprehensive in vivo models of EP biology and therapeutic design.

Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology.

PURPOSE: Glioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted to examine GBM clinically, accurate neuroimaging assessment of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation remains an unmet need in the clinical management of GBMs. EXPERIMENTAL DESIGN: We employ a novel diffusion histology imaging (DHI) approach, combining diffusion basis spectrum imaging (DBSI) and machine learning, to detect, differentiate, and quantify areas of high cellularity, tumor necrosis, and tumor infiltration in GBM. RESULTS: Gadolinium-enhanced T1-weighted or hyperintense fluid-attenuated inversion recovery failed to reflect the morphologic complexity underlying tumor in patients with GBM. Contrary to the conventional wisdom that apparent diffusion coefficient (ADC) negatively correlates with increased tumor cellularity, we demonstrate disagreement between ADC and histologically confirmed tumor cellularity in GBM specimens, whereas DBSI-derived restricted isotropic diffusion fraction positively correlated with tumor cellularity in the same specimens. By incorporating DBSI metrics as classifiers for a supervised machine learning algorithm, we accurately predicted high tumor cellularity, tumor necrosis, and tumor infiltration with 87.5%, 89.0%, and 93.4% accuracy, respectively. CONCLUSIONS: Our results suggest that DHI could serve as a favorable alternative to current neuroimaging techniques in guiding biopsy or surgery as well as monitoring therapeutic response in the treatment of GBM.

Deep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions.

OBJECTIVE: Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterogeneity. We hypothesized that the profiles of multiple DBSI metrics can identify lesion-defining patterns. Here we test this hypothesis by combining a deep learning algorithm using deep neural network (DNN) with DBSI and other imaging methods. METHODS: Thirty-eight MS patients were scanned with diffusion-weighted imaging, magnetization transfer imaging, and standard conventional MRI sequences (cMRI). A total of 499 regions of interest were identified on standard MRI and labeled as persistent black holes (PBH), persistent gray holes (PGH), acute black holes (ABH), acute gray holes (AGH), nonblack or gray holes (NBH), and normal appearing white matter (NAWM). DBSI, diffusion tensor imaging (DTI), and magnetization transfer ratio (MTR) were applied to the 43,261 imaging voxels extracted from these ROIs. The optimized DNN with 10 fully connected hidden layers was trained using the imaging metrics of the lesion subtypes and NAWM. RESULTS: Concordance, sensitivity, specificity, and accuracy were determined for the different imaging methods. DBSI-DNN derived lesion classification achieved 93.4% overall concordance with predetermined lesion types, compared with 80.2% for DTI-DNN model, 78.3% for MTR-DNN model, and 74.2% for cMRI-DNN model. DBSI-DNN also produced the highest specificity, sensitivity, and accuracy. CONCLUSIONS: DBSI-DNN improves the classification of different MS lesion subtypes, which could aid clinical decision making. The efficacy and efficiency of DBSI-DNN shows great promise for clinical applications in automatic MS lesion detection and classification.

The impact of high-dose opioid prescription on mortality rates among people living with HIV: A retrospective cohort study.

OBJECTIVES: High-dose opioid use is associated with increased morbidity, mortality, and healthcare utilization. People living with HIV (PLHIV) are frequently prescribed these medications to manage their pain. However, little is known about the relationship between being prescribed high doses of opioids (> 90 MME/d) and mortality risk among this population. The objective of this study was to examine the trends in mortality and the relationship between high-dose opioid analgesic prescribing and mortality among PLHIV. METHODS: Utilizing the STOP HIV/AIDS cohort--a population-level linked database of treatment of PLHIV in British Columbia--we conducted bivariable and multivariable generalized estimating equation (GEE) models with a Poisson distribution to examine the relationship between high-dose opioid prescription and all-cause mortality rates in the study sample. RESULTS: Between 1996 and 2015, 9272 PLHIV were included in the study. Age- and sex-adjusted mortality rate (using the 2011 Canadian population as the reference) was 30.99 per 1000 person-years (95% confidence interval [CI]: 28.11-33.88). In a multivariable GEE model with adjustment for various demographic and clinical confounders, there was a positive and independent association between being prescribed high-dose opioids and all-cause mortality rates (adjusted rate ratio [ARR] = 3.01; 95%CI: 2.47-3.66). DISCUSSION: We found that mortality rates were significantly higher among PLHIV who were prescribed high-dose opioids compared to those who were prescribed lower doses. Our results highlight the risk associated with the prescribing of high-dose opioids to manage HIV-related pain and emphasize the need to explore non-opioid approaches to pain management.

Sonogenetic Modulation of Cellular Activities Using an Engineered Auditory-Sensing Protein.

Biomolecules that respond to different external stimuli enable the remote control of genetically modified cells. We report herein a sonogenetic approach that can manipulate target cell activities by focused ultrasound stimulation. This system requires an ultrasound-responsive protein derived from an engineered auditory-sensing protein prestin. Heterologous expression of mouse prestin containing two parallel amino acid substitutions, N7T and N308S, that frequently exist in prestins from echolocating species endowed transfected mammalian cells with the ability to sense ultrasound. An ultrasound pulse of low frequency and low pressure efficiently evoked cellular calcium responses after transfecting with prestin(N7T, N308S). Moreover, pulsed ultrasound can also noninvasively stimulate target neurons expressing prestin(N7T, N308S) in deep regions of mouse brains. Our study delineates how an engineered auditory-sensing protein can cause mammalian cells to sense ultrasound stimulation. Moreover, our sonogenetic tools will serve as new strategies for noninvasive therapy in deep tissues.

Delivery of nitric oxide with a nanocarrier promotes tumour vessel normalization and potentiates anti-cancer therapies.

Abnormal tumour vasculature has a significant impact on tumour progression and response to therapy. Nitric oxide (NO) regulates angiogenesis and maintains vascular homeostasis and, thus, can be delivered to normalize tumour vasculature. However, a NO-delivery system with a prolonged half-life and a sustained release mechanism is currently lacking. Here we report the development of NanoNO, a nanoscale carrier that enables sustained NO release to efficiently deliver NO into hepatocellular carcinoma. Low-dose NanoNO normalizes tumour vessels and improves the delivery and effectiveness of chemotherapeutics and tumour necrosis factor-related, apoptosis-inducing, ligand-based therapy in both primary tumours and metastases. Furthermore, low-dose NanoNO reprogrammes the immunosuppressive tumour microenvironment toward an immunostimulatory phenotype, thereby improving the efficacy of cancer vaccine immunotherapy. Our findings demonstrate the ability of nanoscale NO delivery to efficiently reprogramme tumour vasculature and immune microenvironments to overcome resistance to cancer therapy, resulting in a therapeutic benefit.

Prescription of High-Dose Opioids Among People Living with HIV in British Columbia, Canada.

People living with HIV (PLHIV) often experience pain for which opioid medications may be prescribed. Thus, these individuals are particularly vulnerable to opioid-related harms, including overdose, misuse, and addiction, particularly when prescribed at high doses. We used a comprehensive linked population-level database of PLHIV in British Columbia (BC) to identify demographic and clinical characteristics associated with being prescribed any high-dose opioid analgesic, defined as > 90 daily morphine milligram equivalents (MME/day). Among PLHIV who were prescribed opioids between 1996 and 2015 (n = 10,780), 28.2% received prescriptions of > 90 MME/day at least once during the study period. Factors positively associated with being prescribed high-dose opioid analgesics included: co-prescription of benzodiazepines (adjusted odds ratio [AOR] = 1.14; 95% confidence interval 1.11-1.17); presence of an AIDS-defining illness (ADI; AOR = 1.78; 95% CI 1.57-2.02); seen by an HIV specialist (AOR = 1.24; 95% CI 1.20-1.29); substance use disorder (AOR = 1.46; 95% CI 1.25-1.71); and more recent calendar year (AOR = 1.05; 95% CI 1.04-1.06). Given the known risks associated with high-dose opioid prescribing, future research efforts should focus on the clinical indication and outcomes associated with these prescribing practices.

Impact of personality disorders on leaving hospital against medical advice among people living with HIV in British Columbia, Canada.

PURPOSE: Leaving hospital against medical advice (AMA) is a significant source of morbidity, mortality, and a major burden to the healthcare system. Studies have indicated that marginalized populations, including people living with HIV (PLHIV) and those living with a personality disorder (PD), experience high hospitalization rates. We sought to identify whether being diagnosed with a PD was associated with leaving hospital AMA among PLHIV in British Columbia (BC), Canada. METHODS: Data were derived from the STOP HIV/AIDS in BC cohort, a provincial-level linkage of a series of surveillance, laboratory, and health administrative databases of all identified PLHIV in BC. Using multivariable generalized estimating equations (GEE), we examined the relationship between diagnoses of PD and premature hospital discharge among PLHIV. RESULTS: Among 8763 PLHIV included in the study sample, 1321 (15%) were diagnosed with a PD. The prevalence of leaving hospital AMA at least once during the study period was 9%. In multivariable GEE analyses, after adjusting for a range of demographic and clinical confounders, there remained a positive association between being diagnosed with a PD and leaving hospital prematurely. Results showed a significant and independent association between a PD diagnosis and leaving AMA among PLHIV. CONCLUSIONS: These findings underscore the importance of identifying and addressing specific PD-related behaviour which negatively impact inpatient treatment completion among this subpopulation of PLHIV. Furthermore, these findings suggest a need to develop novel health system interventions to minimize AMA discharge among this population.

Correlates of opioid and benzodiazepine co-prescription among people living with HIV in British Columbia, Canada: A population-level cohort study.

BACKGROUND: Co-prescribing benzodiazepines and opioids is relatively contraindicated due to the possible overdose risk. However, people living with HIV (PLWH) may have concurrent psychiatric and/or chronic pain diagnoses that may lead to the use of opioids and/or benzodiazepines for symptomatic treatment. Consequently, some PLWH may be at-risk for the health harms associated with the co-prescribing of these medications. Given this, the objectives of this study were to first examine the prevalence of opioids and benzodiazepines co-prescribing, and second, to characterize patient factors associated with the co-prescribing of opioids and benzodiazepines among PLWH in British Columbia (BC), Canada. METHODS: Using data derived from a longitudinal BC cohort, we used bivariable and multivariable generalized estimating equation models to establish the prevalence of a benzodiazepine and opioid co-prescription and determine factors associated with this practice. RESULTS: Between 1996 and 2015, 14 484 PLWH were included in the study and were followed for the entire study period. At baseline, 548 people (4%) were co-prescribed opioids and benzodiazepines, 6593 (46%) were prescribed opioids only, 2887 (20%) were prescribed benzodiazepines only, and 4456 (31%) were prescribed neither medication. A total of 3835 (27%) participants were prescribed both medications at least once during the study period. Factors positively associated with concurrent opioid and benzodiazepine prescribing included: depression/mood disorder [adjusted odds ratio (AOR) = 1.32; 95% confidence interval (CI) = 1.22-1.43] and anxiety disorder (AOR = 1.45; 95% CI = 1.27-1.66), whereas female sex (AOR = 0.76; 95% CI = 0.64-0.91) and substance use disorder (SUD) (AOR = 0.82; 95% CI = 0.74-0.90) were negatively associated with the outcome. CONCLUSION: Our findings indicate that co-prescription of opioids and benzodiazepines was seen at some point during study follow-up in over a quarter of PLWH. Given the known risks associated with this prescribing practice, future research can focus on the outcomes of co-prescribing among this patient population and the development of strategies to reduce the co-prescribing of opioids and benzodiazepines.

Proteomic Analysis of Extracellular Vesicles for Cancer Diagnostics.

Extracellular vesicles (EVs) including exosomes and microvesicles are lipid bilayer-encapsulated nanoparticles released by cells, ranging from 40 nm to several microns in diameter. Biological cargoes including proteins, RNAs, and DNAs can be ferried by EVs to neighboring and distant cells via biofluids, serving as a means of cell-to-cell communication under normal and pathological conditions, especially cancers. On the other hand, EVs have been investigated as a novel "information capsule" for early disease detection and monitoring via liquid biopsy. This review summarizes current advancements in EV subtype characterization, cancer EV capture, proteomic analysis technologies, as well as possible EV-based multiomics for cancer diagnostics.

Combined delivery of sorafenib and a MEK inhibitor using CXCR4-targeted nanoparticles reduces hepatic fibrosis and prevents tumor development.

Liver damage and fibrosis are precursors of hepatocellular carcinoma (HCC). In HCC patients, sorafenib-a multikinase inhibitor drug-has been reported to exert anti-fibrotic activity. However, incomplete inhibition of RAF activity by sorafenib may also induce paradoxical activation of the mitogen-activated protein kinase (MAPK) pathway in malignant cells. The consequence of this effect in non-malignant disease (hepatic fibrosis) remains unknown. This study aimed to examine the effects of sorafenib on activated hepatic stellate cells (HSCs), and develop effective therapeutic approaches to treat liver fibrosis and prevent cancer development. Methods: We first examined the effects of sorafenib in combination with MEK inhibitors on fibrosis pathogenesis in vitro and in vivo. To improve the bioavailability and absorption by activated HSCs, we developed CXCR4-targeted nanoparticles (NPs) to co-deliver sorafenib and a MEK inhibitor to mice with liver damage. Results: We found that sorafenib induced MAPK activation in HSCs, and promoted their myofibroblast differentiation. Combining sorafenib with a MEK inhibitor suppressed both paradoxical MAPK activation and HSC activation in vitro, and alleviated liver fibrosis in a CCl4-induced murine model of liver damage. Furthermore, treatment with sorafenib/MEK inhibitor-loaded CXCR4-targeted NPs significantly suppressed hepatic fibrosis progression and further prevented fibrosis-associated HCC development and liver metastasis. Conclusions: Our results show that combined delivery of sorafenib and a MEK inhibitor via CXCR4-targeted NPs can prevent activation of ERK in activated HSCs and has anti-fibrotic effects in the CCl4-induced murine model. Targeting HSCs represents a promising strategy to prevent the development and progression of fibrosis-associated HCC.

Tracking Extracellular Vesicles Delivery and RNA Translation Using Multiplexed Reporters.

Elucidating extracellular vesicle (EV; e.g., exosomes, microvesicles) delivery and translation of its RNA cargo with an accurate spatiotemporal resolution is critical in helping understand EV's role under normal and pathological conditions. We here describe a multiplexed fluorescent and bioluminescent reporter strategy to simultaneously monitor and quantify EV delivery, as well as EV-RNA translation in EV-recipient cells.

A Web Tool for Generating High Quality Machine-readable Biological Pathways.

PathWhiz is a web server built to facilitate the creation of colorful, interactive, visually pleasing pathway diagrams that are rich in biological information. The pathways generated by this online application are machine-readable and fully compatible with essentially all web-browsers and computer operating systems. It uses a specially developed, web-enabled pathway drawing interface that permits the selection and placement of different combinations of pre-drawn biological or biochemical entities to depict reactions, interactions, transport processes and binding events. This palette of entities consists of chemical compounds, proteins, nucleic acids, cellular membranes, subcellular structures, tissues, and organs. All of the visual elements in it can be interactively adjusted and customized. Furthermore, because this tool is a web server, all pathways and pathway elements are publicly accessible. This kind of pathway "crowd sourcing" means that PathWhiz already contains a large and rapidly growing collection of previously drawn pathways and pathway elements. Here we describe a protocol for the quick and easy creation of new pathways and the alteration of existing pathways. To further facilitate pathway editing and creation, the tool contains replication and propagation functions. The replication function allows existing pathways to be used as templates to create or edit new pathways. The propagation function allows one to take an existing pathway and automatically propagate it across different species. Pathways created with this tool can be "re-styled" into different formats (KEGG-like or text-book like), colored with different backgrounds, exported to BioPAX, SBGN-ML, SBML, or PWML data exchange formats, and downloaded as PNG or SVG images. The pathways can easily be incorporated into online databases, integrated into presentations, posters or publications, or used exclusively for online visualization and exploration. This protocol has been successfully applied to generate over 2,000 pathway diagrams, which are now found in many online databases including HMDB, DrugBank, SMPDB, and ECMDB.

A spreadsheet calculator for estimating biogas production and economic measures for UK-based farm-fed anaerobic digesters.

This paper presents a spreadsheet calculator to estimate biogas production and the operational revenue and costs for UK-based farm-fed anaerobic digesters. There exist sophisticated biogas production models in published literature, but the application of these in farm-fed anaerobic digesters is often impractical. This is due to the limited measuring devices, financial constraints, and the operators being non-experts in anaerobic digestion. The proposed biogas production model is designed to use the measured process variables typically available at farm-fed digesters, accounting for the effects of retention time, temperature and imperfect mixing. The estimation of the operational revenue and costs allow the owners to assess the most profitable approach to run the process. This would support the sustained use of the technology. The calculator is first compared with literature reported data, and then applied to the digester unit on a UK Farm to demonstrate its use in a practical setting.

Using DrugBank for In Silico Drug Exploration and Discovery.

DrugBank is a fully curated drug and drug target database that contains 8174 drug entries including 1944 FDA approved small-molecule drugs, 198 FDA-approved biotech (protein/peptide) drugs, 93 nutraceuticals, and over 6000 experimental drugs. Additionally, 4300 non-redundant protein (i.e., drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. DrugBank is primarily focused on providing both the query/search tools and biophysical data needed to facilitate drug discovery and drug development. This unit provides readers with a detailed description of how to effectively use the DrugBank database and how to navigate through the DrugBank Web site. It also provides specific examples of how to find chemical homologs of potential drug leads and how to identify potential drug targets from newly sequenced tumor samples. The intent of this unit is to give readers an introduction to the field of Web-based drug discovery and to show how cheminformatics can be seamlessly integrated into the field of bioinformatics. © 2016 by John Wiley & Sons, Inc.