The field of human building interaction for convergent research and innovation for intelligent built environments.

Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops. Three primary areas contribute to and require attention in HBI research: humans (human experiences, performance, and well-being), buildings (building design and operations), and technologies (sensing, inference, and awareness). Three critical interdisciplinary research domains intersect these areas: control systems and decision making, trust and collaboration, and modeling and simulation. Finally, at the core, it is vital for HBI research to center on and support equity, privacy, and sustainability. Compelling research questions are posed for each primary area, research domain, and core principle. State-of-the-art methods used in HBI studies are discussed, and examples of original research are offered to illustrate opportunities for the advancement of HBI research.

Abundance of P-glycoprotein and Breast Cancer Resistance Protein Measured by Targeted Proteomics in Human Epileptogenic Brain Tissue.

Our goal was to measure the absolute differential abundance of key drug transporters in human epileptogenic brain tissue and to compare them between patients and at various distances from the epileptogenic zone within the same patient. Transporter protein abundance was quantified in brain tissue homogenates from patients who underwent epilepsy surgery, using targeted proteomics, and correlations with clinical and tissue characteristics were assessed. Fourteen brain samples (including four epileptogenic hippocampal samples) were collected from nine patients. Among the quantifiable drug transporters, the abundance (median, range) ranked: breast cancer resistance protein (ABCG2/BCRP; 0.55, 0.01-3.26 pmol/g tissue) > P-glycoprotein (ABCB1/MDR1; 0.30, 0.02-1.15 pmol/g tissue) > equilibrative nucleoside transporter 1 (SLC29A1/ENT1; 0.06, 0.001-0.35 pmol/g tissue). The ABCB1/ABCG2 ratio (mean 0.27, range 0.08-0.47) was comparable with literature values from nonepileptogenic brain tissue (mean 0.5-0.8). Transporter abundance was lower in the hippocampi than in the less epileptogenic neocortex of the same patients. ABCG2/BCRP and ABCB1/MDR1 expression strongly correlated with that of glucose transporter 1 (SLC2A1/GLUT1) (r = 0.97, p < 0.001; r = 0.90, p < 0.01, respectively). Low transporter abundance was found in patients with overt vascular pathology, whereas the highest abundance was seen in a sample with normally appearing blood vessels. In conclusion, drug transporter abundance highly varies across patients and between epileptogenic and less epileptogenic brain tissue of the same patient. The strong correlation in abundance of ABCB1/MDR1, ABCG2/BCRP, and SLC2A1/GLUT1 suggests variation in the content of the functional vasculature within the tissue samples. The epileptogenic tissue can be depleted of key drug transport mechanisms, warranting consideration when selecting treatments for patients with drug-resistant epilepsy.

Abundance of P-Glycoprotein and Other Drug Transporters at the Human Blood-Brain Barrier in Alzheimer's Disease: A Quantitative Targeted Proteomic Study.

The human blood-brain barrier (BBB) transporter P-gp can efflux amyloid-ß (Aß) out of the central nervous system (CNS). Aß is thought to be the causative agent for Alzheimer's disease (AD). Using positron emission tomography imaging, we have shown that BBB P-gp activity is reduced in AD, as quantified by the in vivo brain distribution of the P-gp probe [11 C]-verapamil. Therefore, the aim of this study was to determine whether this reduced BBB P-gp activity in AD was due to decreased P-gp abundance at the BBB. Using targeted proteomics, we quantified the abundance of P-gp and other drug transporters in gray matter brain microvessels isolated from 43 subjects with AD and 38 age-matched controls (AMCs) from regions affected by AD (hippocampus and the parietal lobe of the brain cortex) and not affected by AD (cerebellum). First, P-gp abundance was decreased in the BBB of the hippocampus vs. the cerebellum in both subjects with AD and AMCs, and therefore was not AD-related. In addition, gray matter BBB abundance of P-gp (and of other transporters) in the hippocampus and the parietal lobe was not different between AD and AMC. The gray matter BBB abundance of all drug transporters decreased with age, likely due to age-dependent decrease in the density of brain microvessels. Collectively, the observed reduced in vivo cerebral BBB P-gp activity in AD cannot be explained by reduced abundance of P-gp at the BBB. Nevertheless, the drug transporter abundance at the human gray matter BBB data provided here can be used to predict brain distribution of drugs targeted to treat CNS diseases, including AD.

Positron Emission Tomography Imaging of [11 C]Rosuvastatin Hepatic Concentrations and Hepatobiliary Transport in Humans in the Absence and Presence of Cyclosporin A.

Using positron emission tomography imaging, we determined the hepatic concentrations and hepatobiliary transport of [11 C]rosuvastatin (RSV; i.v. injection) in the absence (n = 6) and presence (n = 4 of 6) of cyclosporin A (CsA; i.v. infusion) following a therapeutic dose of unlabeled RSV (5 mg, p.o.) in healthy human volunteers. The sinusoidal uptake, sinusoidal efflux, and biliary efflux clearance (CL; mL/minute) of [11 C]RSV, estimated through compartment modeling were 1,205.6 ± 384.8, 16.2 ± 11.2, and 5.1 ± 1.8, respectively (n = 6). CsA (blood concentration: 2.77 ± 0.24 µM), an organic-anion-transporting polypeptide, Na+ -taurocholate cotransporting polypeptide, and breast cancer resistance protein inhibitor increased [11 C]RSV systemic blood exposure (45%; P < 0.05), reduced its biliary efflux CL (52%; P < 0.05) and hepatic uptake (25%; P > 0.05) but did not affect its distribution into the kidneys. CsA increased plasma concentrations of coproporphyrin I and III and total bilirubin by 297 ± 69%, 384 ± 102%, and 81 ± 39%, respectively (P < 0.05). These data can be used in the future to verify predictions of hepatic concentrations and hepatobiliary transport of RSV.

Interindividual and Regional Variability in Drug Transporter Abundance at the Human Blood-Brain Barrier Measured by Quantitative Targeted Proteomics.

For in vitro to in vivo extrapolation (IVIVE) of brain distribution of drugs that are transported at the human blood-brain barrier (BBB), it is important to quantify the interindividual and regional variability of drug transporter abundance at this barrier. Therefore, using quantitative targeted proteomics, we compared the abundance of adenosine triphosphate-binding cassette and solute carrier transporters in brain microvascular endothelial cells (BMECs) isolated from postmortem specimens of two matched brain regions, the occipital (Brodmann Area (BA)17) and parietal (BA39) lobe, from 30 adults. Of the quantifiable transporters, the abundance ranked: glucose transporter (GLUT)1 > breast cancer resistance protein > P-glycoprotein (P-gp) > equilibrative nucleoside transporter (ENT)1 > organic anion-transporting polypeptide (OATP)2B1. The abundance of multidrug resistance protein 1/2/3/4, OATP1A2, organic anion transporter (OAT)3, organic cation transporter (OCT)1/2, OCTN1/2, or ENT2 was below the limit of quantification. Transporter abundance per gram of tissue (scaled using GLUT1 abundance in BMEC vs. brain homogenate) in BA17 was 30-42% higher than BA39. The interindividual variability in transporter abundance (percentage of coefficient of variation (%CV)) was 35-57% (BA17) and 27-46% (BA39). These data can be used in proteomics-informed bottom-up IVIVE to predict human brain drug distribution.

Targeted LC-MS/MS Proteomics-Based Strategy To Characterize in Vitro Models Used in Drug Metabolism and Transport Studies.

Subcellular fractionation of tissue homogenate provides enriched in vitro models (e.g., microsomes, cytosol, or membranes), which are routinely used in the drug metabolism or transporter activity and protein abundance studies. However, batch-to-batch or interlaboratory variability in the recovery, enrichment, and purity of the subcellular fractions can affect performance of in vitro models leading to inaccurate in vitro to in vivo extrapolation (IVIVE) of drug clearance. To evaluate the quality of subcellular fractions, we developed a simple, targeted, and sensitive LC-MS/MS proteomics-based strategy, which relies on determination of protein markers of various cellular organelles, i.e., plasma membrane, cytosol, nuclei, mitochondria, endoplasmic reticulum (ER), lysosomes, peroxisomes, cytoskeleton, and exosomes. Application of the quantitative proteomics method confirmed a significant effect of processing variables (i.e., homogenization method and centrifugation speed) on the recovery, enrichment, and purity of isolated proteins in microsomes and cytosol. Particularly, markers of endoplasmic reticulum lumen and mitochondrial lumen were enriched in the cytosolic fractions as a result of their release during homogenization. Similarly, the relative recovery and composition of the total membrane fraction isolated from cell vs tissue samples was quantitatively different and should be considered in IVIVE. Further, analysis of exosomes isolated from sandwich-cultured hepatocyte media showed the effect of culture duration on compositions of purified exosomes. Therefore, the quantitative proteomics-based strategy developed here can be applied for efficient and simultaneous determination of multiple protein markers of various cellular organelles when compared to antibody- or activity-based assays and can be used for quality control of subcellular fractionation procedures including in vitro model development for drug metabolism and transport studies.

The Importance of Incorporating OCT2 Plasma Membrane Expression and Membrane Potential in IVIVE of Metformin Renal Secretory Clearance.

Transporter expression, determined by quantitative proteomics, together with PBPK models is a promising approach for in vitro-to-in vivo extrapolation (IVIVE) of transporter-mediated drug clearance. OCT2-expressing HEK293 and MDCKII cells were used to predict in vivo renal secretory clearance (CLr,sec) of metformin. [14C]-Metformin uptake clearance in OCT2-expressing cells was determined and scaled to in vivo CLr,sec by using OCT2 expression in the cells versus the human kidney cortex. Through quantitative targeted proteomics, the total expression of OCT2 in HEK293, MDCKII cells, and human kidney cortex was 369.4 ± 26.8, 19 ± 1.1, and 7.6 ± 3.8 pmol/mg cellular protein, respectively. The expression of OCT2 in the plasma membrane of HEK293 and MDCKII cells, measured using an optimized biotinylation method followed by quantitative proteomics, was 30.2% and 51.6%, respectively. After correcting for percent of OCT2 expressed in the plasma membrane and the resting membrane potential (millivolts) difference between the OCT2-expressing cells and the renal epithelial cells, the predicted CLr,sec of metformin was 250.7 ml/min, a value within the range of the observed CLr,sec of metformin. These data demonstrate the promise of using quantitative proteomics for IVIVE of transporter-mediated drug clearance and highlight the importance of quantifying plasma membrane expression of transporters and utilizing cells that mimic the in vivo mechanism(s) of transport of drugs.

Transporter Expression in Noncancerous and Cancerous Liver Tissue from Donors with Hepatocellular Carcinoma and Chronic Hepatitis C Infection Quantified by LC-MS/MS Proteomics.

Protein expression of major hepatobiliary drug transporters (NTCP, OATPs, OCT1, BSEP, BCRP, MATE1, MRPs, and P-gp) in cancerous (C, n = 8) and adjacent noncancerous (NC, n = 33) liver tissues obtained from patients with chronic hepatitis C with hepatocellular carcinoma (HCV-HCC) were quantified by LC-MS/MS proteomics. Herein, we compare our results with our previous data from noninfected, noncirrhotic (control, n = 36) and HCV-cirrhotic (n = 30) livers. The amount of membrane protein yielded from NC and C HCV-HCC tissues decreased (31%, 67%) relative to control livers. In comparison with control livers, with the exception of NTCP, MRP2, and MATE1, transporter expression decreased in NC (38%-76%) and C (56%-96%) HCV-HCC tissues. In NC HCV-HCC tissues, NTCP expression increased (113%), MATE1 expression decreased (58%), and MRP2 expression was unchanged relative to control livers. In C HCV-HCC tissues, NTCP and MRP2 expression decreased (63%, 56%) and MATE1 expression was unchanged relative to control livers. Compared with HCV-cirrhotic livers, aside from NTCP, OCT1, BSEP, and MRP2, transporter expression decreased in NC (41%-71%) and C (54%-89%) HCV-HCC tissues. In NC HCV-HCC tissues, NTCP and MRP2 expression increased (362%, 142%), whereas OCT1 and BSEP expression was unchanged. In C HCV-HCC tissues, OCT1 and BSEP expression decreased (90%, 80%) relative to HCV-cirrhotic livers, whereas NTCP and MRP2 expression was unchanged. Expression of OATP2B1, BSEP, MRP2, and MRP3 decreased (56%-72%) in C HCV-HCC tissues in comparison with matched NC tissues (n = 8), but the expression of other transporters was unchanged. These data will be helpful in the future to predict transporter-mediated hepatocellular drug concentrations in patients with HCV-HCC.

Microsomal and Cytosolic Scaling Factors in Dog and Human Kidney Cortex and Application for In Vitro-In Vivo Extrapolation of Renal Metabolic Clearance.

In vitro-in vivo extrapolation of drug metabolism data obtained in enriched preparations of subcellular fractions rely on robust estimates of physiologically relevant scaling factors for the prediction of clearance in vivo. The purpose of the current study was to measure the microsomal and cytosolic protein per gram of kidney (MPPGK and CPPGK) in dog and human kidney cortex using appropriate protein recovery marker and evaluate functional activity of human cortex microsomes. Cytochrome P450 (CYP) content and glucose-6-phosphatase (G6Pase) activity were used as microsomal protein markers, whereas glutathione-S-transferase activity was a cytosolic marker. Functional activity of human microsomal samples was assessed by measuring mycophenolic acid glucuronidation. MPPGK was 33.9 and 44.0 mg/g in dog kidney cortex, and 41.1 and 63.6 mg/g in dog liver (n = 17), using P450 content and G6Pase activity, respectively. No trends were noted between kidney, liver, and intestinal scalars from the same animals. Species differences were evident, as human MPPGK and CPPGK were 26.2 and 53.3 mg/g in kidney cortex (n = 38), respectively. MPPGK was 2-fold greater than the commonly used in vitro-in vivo extrapolation scalar; this difference was attributed mainly to tissue source (mixed kidney regions versus cortex). Robust human MPPGK and CPPGK scalars were measured for the first time. The work emphasized the importance of regional differences (cortex versus whole kidney-specific MPPGK, tissue weight, and blood flow) and a need to account for these to improve assessment of renal metabolic clearance and its extrapolation to in vivo.

Assessment of models for anaerobic biodegradation of a model bioplastic: Poly(hydroxybutyrate-co-hydroxyvalerate).

Kinetic models of anaerobic digestion (AD) are widely applied to soluble and particulate substrates, but have not been systematically evaluated for bioplastics. Here, five models are evaluated to determine their suitability for modeling of anaerobic biodegradation of the bioplastic poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV): (1) first-order kinetics with and without a lag phase, (2) two-step first-order, (3) Monod (4) Contois, and (5) Gompertz. Three models that couple biomass growth with substrate hydrolysis (Monod, Contois, and Gompertz) gave the best overall fits for the data (R2>0.98), with reasonable estimates of ultimate CH4 production. The particle size limits of these models were then evaluated. Below a particle size of 0.8mm, rates of hydrolysis and acetogenesis exceeded rates of methanogenesis with accumulation of intermediates leading to a temporary inhibition of CH4 production. Based on model fit and simplicity, the Gompertz model is recommended for applications in which particle size is greater than 0.8mm.

Abundance of Drug Transporters in the Human Kidney Cortex as Quantified by Quantitative Targeted Proteomics.

Protein expression of renal uptake and efflux transporters was quantified by quantitative targeted proteomics using the surrogate peptide approach. Renal uptake transporters assessed in this study included organic anion transporters (OAT1-OAT4), organic cation transporter 2 (OCT2), organic/carnitine cation transporters (OCTN1 and OCTN2), and sodium-glucose transporter 2 (SGLT2); efflux transporters included P-glycoprotein, breast cancer resistance protein, multidrug resistance proteins (MRP2 and MRP4), and multidrug and toxin extrusion proteins (MATE1 and MATE2-K). Total membrane was isolated from the cortex of human kidneys (N = 41). The isolated membranes were digested by trypsin and the digest was subjected to liquid chromatography-tandem mass spectrometry analysis. The mean expression of surrogate peptides was as follows (given with the standard deviation, in picomoles per milligram of total membrane protein): OAT1 (5.3 ± 1.9), OAT2 (0.9 ± 0.3), OAT3 (3.5 ± 1.6), OAT4 (0.5 ± 0.2), OCT2 (7.4 ± 2.8), OCTN1 (1.3 ± 0.6), OCTN2 (0.6 ± 0.2), P-glycoprotein (2.1 ± 0.8), MRP2 (1.4 ± 0.6), MRP4 (0.9 ± 0.6), MATE1 (5.1 ± 2.3), and SGLT2 (3.7 ± 1.8). Breast cancer resistance protein (BCRP) and MATE2-K proteins were detectable but were below the lower limit of quantification. Interestingly, the protein expression of OAT1 and OAT3 was significantly correlated (r > 0.8). A significant correlation was also observed between expression of multiple other drug transporters, such as OATs/OCT2 or OCTN1/OCTN2, and SGLT2/OCTNs, OCT, OATs, and MRP2. These renal transporter data should be useful in deriving in vitro to in vivo scaling factors to accurately predict renal clearance and kidney epithelial cell exposure to drugs or their metabolites.