We present a new method of chemical quantification utilizing thermal analysis for the detection of relative humidity. By measuring the temperature change of a hydrophilically-modified temperature sensing element vs. a hydrophobically-modified reference element, the total heat from chemical interactions in the sensing element can be measured and used to calculate a change in relative humidity. We have probed the concept by assuming constant temperature streams, and having constant reference humidity (~0% in this case). The concept has been probed with the two methods presented here: (1) a thermistor-based method and (2) a thermographic method. For the first method, a hydrophilically-modified thermistor was used, and a detection range of 0–75% relative humidity was demonstrated. For the second method, a hydrophilically-modified disposable surface (sensing element) and thermal camera were used, and thermal signatures for different relative humidity were demonstrated. These new methods offer opportunities in either chemically harsh environments or in rapidly changing environments. For sensing humidity in a chemically harsh environment, a hydrophilically-modified thermistor can provide a sensing method, eliminating the exposure of metallic contacts, which can be easily corroded by the environment. On the other hand, the thermographic method can be applied with a disposable non-contact sensing element, which is a low-cost upkeep option in environments where damage or fouling is inevitable. In addition, for environments that are rapidly changing, the thermographic method could potentially provide a very rapid humidity measurement as the chemical interactions are rapid and their changes are easily quantified. Although humidity sensing is a well-established field with a range of sensors available at low-cost, high accuracy, or other special applications, humidity sensing in harsh or complex environments is still a challenge. Some examples of harsh environments are sewers and equipment for drying prepared foods. In both of these cases, monitoring humidity may be needed for improved outcomes. For instance, relative humidity is an important factor in predicting corrosion rates in sewers. In the United States alone, it was estimated that sewer corrosion incurs a cost of 14 billion dollars annually ,3,4; morAnother challenging environment for sensing humidity is breath. Breath humidity is important for detection of hydration, and for accurately detecting other parameters related to metabolism , lung fuA thermistor-based chemical sensor, which consists of a surface-treated thermistor, enabling an inexpensive and robust contact method with an accurate low-thermal mass thermistor starting at less than $3 in bulk and simple data-acquisition circuitry, which can be insulated from harsh environments.® One) [A thermographic humidity sensor, which utilizes a thermal camera to image a simple disposable sensing element, enabling a non-contact method of transducing humidity signal. Thermal infrared sensors start at as little as $8 each in bulk and consumer thermal cameras start at as little as $250 (FLIR® One) .In previous works, we have developed disposable humidity sensors based on color change detection for product monitoring . In thisIn both methods, high accuracy can be achieved when applied with a proper reference, such as an uncoated thermistor  or an insulated spot on the disposable imaging element (in the method 2-thermographic humidity sensor). In both approaches, the chemical modification of the thermistor or the disposable imaging agent (sensing element) have a wide variety of sensing options available. In this work, we take advantage of heat interactions involved in the hydration of a neutral salt in the presence of humidity. With this, we demonstrate the effectiveness of thermistor-based chemical detection of humidity and the characterization and effectiveness of thermographic chemical detection of humidity. Thermistor-based method consists of a coated thermistor in a gas stream exposed to alternating samples of dry and humid gas samples see . For theSensing thermistor preparation: The sensing thermistor was prepared by coating a low-thermal mass thermistor  with a solution containing a long-chain quaternary ammonium salt and color dye. The salt provides heat upon hydration and the dye allows for visualization. The thermistor was dip-coated and allowed to dry in ambient lab conditions. Measurements were taken at 40 Hz, with an effective temperature resolution of less than 0.05 Celsius. Humidified gas samples: Humidified samples were made using a humidity controlled environment (Coy Labs). A large chamber was maintained at a humidity set point, and then gas from said environment pumped at a set flow rate over the thermistor. The flow rate was constant for all tests at roughly 3 L/min and the range of relative humidity levels probed was from 0–90% at room temperature.The thermal camera setup utilized a sensor with the same chemistry as in the thermistor-based chemical method. In this case, the hydrophilic sensing mixture was applied in the form of a disposable coated Teflon strip. The Teflon strip was placed in a heated aluminum block see . For theDisposable sensing element: The sensing elements were prepared by coating a porous Teflon membrane with the same mixture as the thermistor. The Teflon is dip-coated and dried, then laminated into an easy-to-handle chip, as seen in blockT. The device was designed such that the sensing element (sensor) sits in the aluminum block and the flow laterally runs over the sensor. The imaging port is located in the opposite side of the sensing element, as seen in gasT. This temperature, together with blockT and the temperature measurements assessed via the thermal camera (see below) on the sensing element (sensorT) were also taken in the gas stream in order to build the heat model used for evaluation. For these measurements, flow rates from 0–32 L/min were considered.Flow measurements and heating: Flow measurements and heating were performed in a custom setup. Flow measurements were performed with a differential pressure flow meter , which also works to protect the sensor from water accumulation. Heating was done with an aluminum block holding the sensor see D. AlthouQ is heat flux, either total or from a contributor  as a differential over time (t). Equation (2) shows the relationship between the total heat and the mass (m), specific heat capacity (c), and the temperature of the sensor (sensorT):The sensing system utilizes heat generation from the hydration of the hydrophilic chemical layer on the sensing element for the quantification of humidity levels. In order to relate the amount of heat generated from humidity interactions, the system needed to be characterized in terms of heat contributions from conduction and convection. Therefore, heat contributions from the three heat sources: conduction, convection, and chemistry were accounted for. Equation (1) shows the overall heat relationship: A is the area, K is the conduction coefficient, surfaceT is the temperature for the block, sensorT is the temperature of the sensor, H(f) is the convection coefficient as a function of the flow rate (f), B is the amount of heat generated per unit change in relative humidity concentration, C is the concentration of humidity on the sensor, and t is time. This form gives explicit contributions from each component in terms of coefficients, which were determined under certain experimental conditions as described in the next sections.By utilizing a reference state of 0 degrees Celsius, we can simplify Equation (2) to what is seen on the right side of the equation. The relationship can be further broken down to Equation (3) as follows:The first characterization of the system was to perform heat tests without a flow in order to determine the conduction and free convection rates. In order to measure changes under these conditions, a sensor at room temperature was placed inside of the heated device, and then the rate of heating recorded via thermal camera. These tests were performed at constant relative humidity with no flow. Under these conditions Equation (3) can be simplified to Equation (4).At steady-state conditions, the net heat flux will be equal to zero, which allows for simplification down to Equation (5).K and H(0) for our system. The analysis yielded a K value of about 36 W/m·K and an H(0) value of about 24 W/m·K.In order to determine the absolute values of the coefficients, the relationship can be solved for non-steady-state conditions, as seen in H) as a function of the flow rate can be obtained, as shown in The next step was to determine the relationship of the convection coefficient as a function of flow rate. This was done by setting a dry gas cylinder to a set flow rate and cycling flow through the setup (on and off), all while recording the temperature changes with the thermal camera. This allows a very straight forward and simple method for assessing the convection coefficient at constant flows, as all temperatures and the conduction coefficient are accounted for in all cases. rabs and rdes are the rates of absorption and desorption, respectively, gasC is the concentration of analyte in the gas surrounding the sensor, and sensorC is the concentration of analyte in the sensing element, where in this case the analyte is humidity.For probing humidity with this setup, the tests can be reframed as the deviation from heat values expected under dry conditions. The heat production will be a function of two factors: the partial pressure of water in the gas and sensor, and the absorption and desorption rates, as shown in Equation (6) as follows:Since the effects of conduction and convection can be calculated, the heat generation from reactivity can be ascertained. In this work, we demonstrate the utility of the humidity detection via thermal analysis. This can provide a robust and inexpensive measurement for application in harsh environments, such as sewers or food processing operations, or in otherwise difficult environments, such as breath. Using a coated thermistor, we demonstrate the ability to discriminate relative humidity in the range of 0–75% by measuring temperature changes. Using a thermal camera and disposable element, we demonstrate a clear signal due to relative humidity change and provide evidence of a relationship between the magnitude of change in relative humidity and the magnitude of the signal. Future work in this area will be directed to specific sensor design to adapt the needs of different sensing scenarios.


PD-1 abundance was weakly correlated  with the fraction of lymphocytes and histiocytes in sections. PD-L2 was measured from 0.03 to 1.90 fmol/microgram protein and the ratio of PD-L2 to PD-L1 abundance ranged from 0.03 to 2.58. In 10 samples, PD-L2 was present at more than half the level of PD-L1, which suggests that PD-L2, a higher affinity PD-1 ligand, is sufficiently abundant to contribute to T-cell downregulation. We also identified five branched mannose and N-acetylglucosamine glycans at PD-L1 position N192 in all 22 samples. Extent of PD-L1 glycan modification varied by ∼10-fold and the melanoma with the highest PD-L1 protein abundance and most abundant glycan modification yielded a very low PD-L1 IHC estimate, thus suggesting that N-glycosylation may affect IHC measurement and PD-L1 function. Additional PRM analyses quantified immune checkpoint/co-regulator proteins LAG3, IDO1, TIM-3, VISTA, and CD40, which all displayed distinct expression independent of PD-1, PD-L1, and PD-L2. Targeted MS can provide a next-generation analysis platform to advance cancer immuno-therapeutic research and diagnostics.Quantitative assessment of key proteins that control the tumor-immune interface is one of the most formidable analytical challenges in immunotherapeutics. We developed a targeted MS platform to quantify programmed cell death-1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and programmed cell death 1 ligand 2 (PD-L2) at fmol/microgram protein levels in formalin fixed, paraffin-embedded sections from 22 human melanomas. PD-L1 abundance ranged 50-fold, from ∼0.03 to 1.5 fmol/microgram protein and the parallel reaction monitoring (PRM) data were largely concordant with total PD-L1-positive cell content, as analyzed by immunohistochemistry (IHC) with the E1L3N antibody. PD-1 was measured at levels up to 20-fold lower than PD-L1, but the abundances were not significantly correlated (r Immune checkpoint proteins, such as programmed cell death 1  and its ligand programmed cell death 1 ligand 1 PD-L1. Inhibit37One of the most critical questions in immuno-oncology is which patients will benefit from immune checkpoint therapeutics. Objective responses are seen in only 15–45% of patients with solid tumors treated with immune checkpoint drugs , which i1722et al. recently noted limitations of available PD-L2 antibodies for IHC and used mRNA transcript data to compare the expression of PD-L2 with PD-L1 and PD-1  also can inactivate T cells by binding to PD-1 . PD-L2 band PD-1 . Measureand PD-1  and by pand PD-1 .Given the well-documented limitations of antibody-based immune checkpoint measurements, we considered measurements based instead on targeted MS by parallel reaction monitoring (PRM), which has emerged as a sensitive, highly specific and robust platform for the quantitative analysis of proteins , 32. PRMHere we describe the development of an addressable fractionation-PRM platform, which provides measurements of PD-1, PD-L1, and PD-L2 at femtomole per microgram tissue protein levels in FFPE sections of human melanoma biopsies. We compared our analyses to IHC measurements of PD-L1 in adjacent sections and further characterized the effects of variable cellular composition on measured PD-1, PD-L1, and PD-L2. Our measurements demonstrate substantial between-tumor variation in expression ratios of these proteins and suggest that PD-L2 is present in some tumors at levels sufficient to contribute to PD-1-dependent T-cell regulation and possibly to affect responses to PD-1- and PD-L1-blocking drugs. We further report the identification and quantitation of several N-glycosylated forms of PD-L1 in the same samples and provide evidence that post-translational modifications of PD-L1 may affect PD-L1 detection by IHC. Finally, we demonstrate the extension of our addressable fractionation-PRM platform to analyze several other immune checkpoint and coregulator proteins, which are targets for new drug development or which affect responses to immunotherapeutics. The data demonstrate the potential utility of targeted MS as a next-generation analysis platform to advance cancer immuno-therapeutic research and diagnostics.13C6, U-15N4-arginine, or U-13C6, U-15N2-lysine and unlabeled peptide standards were purchased from New England Peptide . Isotope labeled peptides were of greater than 99 and 95% isotopic and chemical purity, respectively; absolute concentration was determined by amino acid analysis.Recombinant human PD-L1 protein  and PNGase-F were purchased from Thermo Fisher Scientific  and Promega , respectively. Sep-Pak C18 desalting cartridges  and XBridge C18  columns were from Waters . ReproSil C18-AQ resin (3 μm particle size) was purchased from Dr. Maisch, Gmbh . Picofrit self-pack columns  were from New Objective . An equimolar predigested bovine 6 protein mix used as an MS system performance standard was purchased from Bruker-Michrom, Inc. . Trypsin (Trypsin Gold) was from Promega . C-terminal isotopically labeled peptides containing U-supplemental Table S1. Samples were fixed in 10% buffered neutral formalin, processed and paraffin-embedded by standard methods in automated tissue processor. Five-micrometer sections were subjected to hematoxylin and eosin (H&E) staining and dual IHC using antibodies against PD-L1  and SOX10 . Sections analyzed by hematoxylin and eosin (H&E) staining and IHC were serially adjacent to those analyzed by MS.Tissue sections (5 μm thickness) were obtained from archival FFPE tumor blocks from patients treated for melanoma at Vanderbilt University Medical Center. All participants provided informed consent for use of tissue specimens and the study was approved by the Vanderbilt Institutional Review Board . Participants all received immune checkpoint inhibitors as second or third line therapy. Individual demographic information, therapies and responses, biopsy site(s) sampled and other relevant information are provided in Tissue was incubated overnight at 4 °C with both rabbit monoclonal antibody against PD-L1  and mouse monoclonal antibody against SOX-10 .  Antigen retrieval was performed using Citrate Buffer pH6 (Biocare Decloaking Chamber). Visualization was preformed using MACH2 system (Biocare), DAB (SOX10) and Fast Red (PD-L1) as chromogens, and counterstained with hematoxylin. The slides were scanned using a high-resolution scanner (Leica SCN400 Slide Scanner) at 20× magnification. PD-L1 was scored and expressed as a percentage of stained cells for tumor cells, peri- and intratumoral immune infiltrate (mostly mononuclear phagocytic cells), and other nontumor tissue cells.2. Cells were harvested, washed twice in phosphate-buffered saline, and frozen at 80 °C until used. Frozen cell pellets were lysed on ice in 8 m urea supplemented with 1× HALT protease and phosphatase inhibitor (Life Technologies). Lysates were clarified by centrifugation at 10,000 × g for 10 min at 4 °C and desalted with a Sep-Pak C18 1cc Vac Cartridge . Protein in the lysates was measured with the bicinchoninic acid (BCA) assay .HEK-293 cells  were grown in DMEM  supplemented with 10% fetal bovine serum  at 37 °C in a humidified atmosphere with 5% COm ammonium bicarbonate, pH 8.0 (AmBic). Proteins were extracted from the rehydrated specimens by a two-step procedure. First, 100 μl of trifluoroethanol was added to each sample, followed by the addition of 100 μl of AmBic. Each tube was sonicated 3 times continuously for 20 s using a Sonic Dismembrator probe at level 2 , with cooling of samples on ice for 30 s between each sonication step. Samples then were gently shaken for 60 min at 60 °C. For the second extraction step, 100 μl of 10 m urea was added to each tube and sonication steps, described above, were repeated. Samples then were gently shaken for 60 min at 60 °C. Protein concentration in lysates was measured using the BCA assay .The material from two 5 μm FFPE tissue sections was scraped from the glass slides using a clean razor blade and transferred into a clean 1.5 ml Eppendorf tube. FFPE tissue was deparaffinized and hydrated as previously described  with them Ambic, was added to a final concentration of 5 mm and solutions were incubated for 30 min at 60 °C. Iodoacetamide (100 mm prepared in HPLC-grade water) was added to a concentration of 10 mm and the solution was incubated in the dark for 20 min at room temperature. Samples were diluted further with 800 μl of AmBic to achieve final concentrations of ≤10% trifluoroethanol and ≤ 1 m urea before digestion. Trypsin (2 μg) was added to each sample to achieve a 1:50 (w/w) trypsin/protein ratio and the samples were incubated overnight at 37 °C. After 16 h digestion, the samples were frozen at −80 °C and evaporated to dryness under vacuum.For protein digestion, aliquots of lysate corresponding to 100 μg protein were diluted to a volume 200 μl with AmBic. A 50-mM solution of dithiothreitol, prepared in 50 mm triethylamine bicarbonate pH 7.5 (TEAB) in water as solvent A and 10 mm TEAB in 90% acetonitrile as solvent B. The mobile phase was programmed from zero to 5% B in 5 min, from 5% to 35% B in 45 min and then held at 90% B for 10 min before returning to initial conditions. A total of 12 fractions were collected over time slices of 4.75 min each for the first 50 min of the program. The fractions were evaporated to dryness under vacuum and stored at −80 °C until PRM analysis.Dried sample residues were re-suspended in 350 μl deionized water and desalted with an Oasis HLB μElution Plate . Plates were prewashed with 500 μl of acetonitrile and equilibrated with 750 μl of HPLC-grade water. The flow-through was discarded and the plates were washed with 500 μl of HPLC-grade water and the peptides were eluted with 80% acetonitrile. A mixture of 50 fmol each of the isotopically labeled peptide SID and LRP standards (see below) was added to each eluted peptide mixture. The tryptic peptides from the 100 μg digests then were fractionated using bRPLC separation with an Agilent 1260 Infinity HPLC System with a XBridge C18, 250 mm × 4.6 mm analytical column  and a XBridge C18 Sentry guard cartridge at a flow rate of 0.5 ml/min. The mobile phase consisted of 10 mPRM assays were performed on a Q Exactive Plus mass spectrometer  equipped with a Easy nLC1000 LC and autosampler system (ThermoFisher Scientific). For each analysis, 5 μl of each sample was injected onto a PicoFrit capillary column  packed ReproSil-Pur C18 AQ 3 μm resin (Dr. Maisch GmbH). The column was heated to 45 °C. Solvent A was 0.1% formic acid in water and solvent B was 0.1% formic acid in acetonitrile. Peptides were separated at a flow rate of 400 nL/min using a linear gradient of 2% solvent B for 1 min followed by increase to 28% solvent B over 48 min, then to 60% solvent B over 5 min, followed by an increase to 90% solvent B. The mobile phase was then held at that composition for 7 min before returning to initial conditions.m/z values. Retention times were determined from prior analyses of synthetic peptide standards. The MS1 scan was collected at a resolution of 17,500, an automatic gain control (AGC) value of 3e6, a max injection time of 64 msec, and a scan range from m/z 380–1500. MS1 data were recorded in profile mode. The MS1 scan was followed by 14 targeted MS2 scans at a resolution of 70,000, an AGC value of 1e6, a max injection time of 240 msec, 0.7 m–z isolation window, fixed first mass of 200 m–z, an optimized collision energy for each target of 20, 23, or 27%. MS2 data were recorded in profile mode. Lists of all peptides targeted in the PRM analyses are provided in supplemental Table S2.The acquisition method consisted of a full scan selected ion monitoring event followed by 14 targeted MS2 scans as triggered by a scheduled inclusion list, with a 5-min retention time window containing the precursor m/z, charge state, normalized collision energy and PRM transitions extracted is presented in supplemental Table S2. Reverse calibration curves were generated for each peptide pair by spiking a constant level of 2.5 fmol/μl of light peptide and heavy peptide standard at concentrations from a low value of 0.01562 fmol/μl to a high value of 10 fmol/μl in 0.56 μg/μl HEK-293 lysate background. Linearity of calibration curves was assessed and an equation for determining the analyte concentration using the peak area ratio of light/heavy isotopologs was defined using QuaSAR , C10orf54 (VISTA), and CD40, including bRPLC fractions, precursor N-linked site was identified based on the difference in mass (0.98 Da) from the native sequence associated with conversion of the asparagine glycosylation site to aspartate after PNGase F treatment.Recombinant human PD-L1 was reduced, alkylated, and digested with trypsin as described above. The digest (100 μg) was treated with 1 μl of protein N-glycanase F  in 25 μl AmBic, with incubation overnight at 37 °C. The PD-L1 N-linked glycopeptides were initially identified by untargeted MS/MS analyses of the tryptic digest of recombinant human PD-L1. The chromatographic retention of heterogeneous N-linked glycopeptides is like that of the corresponding unmodified peptide in reverse phase chromatography, because the primary stationary phase interaction is with the hydrophobic peptide backbone (http://web.expasy.org/glycomod/). The structures of N-linked glycopeptides from both recombinant PD-L1 and from melanoma specimens were manually characterized from MS/MS spectra. Only peak assignments with mass accuracy within 10 ppm of theoretical m/z were accepted for manual characterization.Structures of the intact backbone , 42. Acct test for significance. MS and IHC-measured abundances of PD-L1 were compared by Spearman rank correlation with a two tailed t test for significance. Raw data files can be downloaded at: ftp://massive.ucsd.edu/MSV000080433. Processed Skyline files can be downloaded at https://panoramaweb.org/labkey/Liebler_IO_checkpoints.url.Analyses of the recovery of PD-L1 peptides LQDAGVYR and VNAPYNK from recombinant PD-L1 protein spiked into HEK-293 cell lysates were done in duplicate. Analyses of the reproducibility of measurement of peptides from PD-1, PD-L1, and PD-L2 were done with four full process replicates. Because of limiting amounts of available samples, a single protein preparation and tryptic digest was fractionated for each melanoma sample and each bRPLC fraction was analyzed once by targeted MS. Calibration curves were analyzed with the QuaSAR utility as implemented in Skyline and QuaSAR was used to determine LLOD and LLOQ. MS-measured abundances of PD-1, PD-L1, and PD-L2 peptides were compared by Pearson correlation with a two-tailed supplemental Fig. S1). To improve assay sensitivity, we developed an addressable basic reverse phase fractionation (bRPLC) strategy based on the approach described by Shi et al.  run of unfractionated tryptic digest. These analyses detected PD-L1 proteotypic peptides VNAPYNK and LQDAGVYR, but with low signal intensity, which would likely be inadequate for robust quantitation . The peptides VNAPYNK and LQDAGVYR were released from PD-L1 in a 1:1 ratio, as indicated by Pearson correlation (r = 1.000) for their yields in the spike-recovery experiments . We next performed four full process replicate analyses of a single FFPE melanoma specimen. Coefficients of variation for the measurements were 6.6% , 5.8% , 10.9% , and 20.1%  .To estimate the spike recovery of the SID assays for PD-L1 peptides VNAPYNK and LQDAGVYR, we spiked recombinant human PD-L1 protein at 0, 0.031, 0.063, 0.125, 0.25, 0.5, 1, or 5 fmol in 100 μg HEK-293 cell lysate. Duplicate response curves for both peptides were linear across the spike range with slopes of unity, which corresponded to ∼100% recovery  Micrographs of H&E stained sections and adjacent sections stained for PD-L1 are presented in supplemental Data set S1. The cellular composition of the samples and the fractions of each cell type component that stained positive for PD-L1 are represented in supplemental Table S4. In some samples, most of the PD-L1-positive staining was in tumor cells (e.g. B10 and B29), whereas in others PD-L1 positive staining was primarily in histiocytes  or in other cells, such as alveolar macrophages and skeletal muscle (B7 and B8).We performed IHC analyses with the E1L3N antibody, which recognizes an intracellular epitope near the PD-L1 C terminus. IHC detected PD-L1 immunoreactivity in tumor cells, histiocytes, and tissue macrophages, as well as in peripheral nerves, ganglion cells, skeletal muscle, intestinal epithelial cells and salivary epithelial cells supplemental Data set S2. Peak areas and calculations for peptide quantitation are presented in supplemental Tables S5 and S6.) Measurements for both peptides were above the lower limit of quantitation (LLOQ) in all samples and ranged 50-fold, from ∼0.03 to 1.5 fmol/μg protein. VNAPYNK and LQDAGVYR measurements were highly correlated , but VNAPYNK was often measured at lower abundance (mean 0.85 ± 0.22). This may reflect variable loss of the lysine C-terminal peptide VNAPYNK because of formalin fixation, as we have reported previously . A notable outlier was sample B14 , which indicated little PD-L1 by IHC (3% of entire section), but the highest MS-measured PD-L1 abundance of all the samples.We measured PD-L1 via SID assays for the peptides VNAPYNK and LQDAGVYR, as described above .  with the fraction of lymphocytes/histiocytes in sections. PD-L1 abundance was up to 20-fold greater than PD-1 abundance in samples where both were quantifiable , but the abundances were not significantly correlated . PD-L2 was quantifiable via the peptide TPEGLYQVTSVLR in 18 of the 22 samples and measured values ranged 95-fold from 0.03 to 1.90 fmol/μg protein .PD-1 was quantifiable via the peptide LAAFPEDR in 9 of the 22 samples and measured values ranged 5-fold from 0.03 to 0.15 fmol/μg protein . PD-1 ab protein . The rat protein . In 10 ssupplemental Figs. S4–S6). MS/MS analysis of the tryptic N-glycopeptide forms of LFNVTSTLR, which contains the N192 residue, identified 5 glycan forms . The MS/MS spectra of putative glycopeptides contained characteristic low molecular weight oxonium ions, including m/z 204 (HexNAc+), m/z 366 (Hex-HexNAc+), and m/z 528 (Hex-Hex-HexNAc+). Candidate structures generated from the precursor ion m/z using the GlycoMod tool (http://web.expasy.org/glycomod/) were high-mannose glycans. Although these structures presented in supplemental Figs. S7–S11 are consistent with the MS data, the number and exact identities of isomeric structures for the high mannose glycans cannot be determined from the MS data alone.PD-L1 has been reported to be N-glycosylated at several residues , 44. We supplemental Figs. S7–S11). We also found that all of the glycopeptide forms eluted together in the same bRPLC fraction . This enabled us to design a relative quantitation approach in which the integrated peak areas for the highest intensity MS/MS product ion (LFN(HexNAc)VTSTLR+, m/z 1253.6806) were normalized to the PD-L1 protein amounts calculated from SID measurements of the LQDAGVYR peptide in each sample. PD-L1 N192 glycopeptides were detectable in all the 22 melanomas, with the Man5, Man6, and Man7 structures having the highest relative abundance . The relative abundances for each glycopeptide varied ∼50-fold . Moreover, samples B9, B17, B21, and B28 had no IHC-detectable PD-L1 . Comparisons with the LRP method are based on ratios of the integrated transitions to those of the standard. This permits comparison of relative amounts between samples, but not molar amounts of different proteins in the same sample. . Nevertheless, the LRP analyses detected IDO1, LAG3, TIM-3, VISTA, and CD40 in the 22 melanomas , lymphocyte activating 3 (LAG3), hepatitis A virus cellular receptor 2 (HAVCR2 (TIM-3)), chromosome 10 open reading frame 54 (C10orf54 (VISTA)), and CD40 molecule (CD40). We adapted the labeled reference peptide (LRP) method  for measurements with the two platforms. Nevertheless, cells that exceed a staining intensity threshold may contain substantially different amounts of PD-L1. For example, sample B29 had the highest PD-L1 positive percentage of cells (61%), but had only the fourth highest PD-L1 MS measurement. IHC staining intensity for the tumor cells was only modestly above the detection threshold. Similarly, sample B1 had the third highest IHC rank, with 31% PD-L1 positive cells, but was the 13th highest MS rank for PD-L1 abundance. This specimen showed extended areas with low intensity staining. Thus, although IHC can distinguish tissues with PD-L1 staining above or below a threshold, IHC is nevertheless a poor measure of PD-L1 quantity in tissues.A comparison between the MS and IHC results should consider the different characteristics of the measurements. MS measures molar quantities of PD-L1, whereas IHC measures percentages of cells in a field that exceed a minimum threshold staining intensity. Percentages of cells that exceed the threshold may be proportional to the overall molar amount of PD-L1 in a sample. This was confirmed by the moderate rank correlation  and B8 (primary tumor), PD-L1 positive staining was localized to macrophages and skeletal muscle, respectively. Comparison of the IHC and MS data indicates that the highest MS measurements usually corresponded to samples with a significant fraction of PD-L1 positive tumor cells. Nevertheless, the key point of these comparisons is that the cellular source of MS-measured PD-L1 cannot be assigned to any particular cell type without accompanying IHC measurement.Our studies confirmed PD-L1 N-glycosylation, which has been reported previously , 44, altThese comparisons revealed considerable variability in fractional N192 glycosylation of PD-L1 in the samples. The unmodified N192-containing peptide LFNVTSTLR was not detected in any of the samples in the bRPLC fraction containing an isotope labeled synthetic LFNVTSTLR standard (data not shown). Sample B14 had the highest degree of N192 glycosylation, together with the highest PD-L1 protein abundance, but with little detectable PD-L1 by IHC. This sample was a small intestinal metastasis containing 73% tumor cells, but with PD-L1 positive IHC staining only in histiocytes, peripheral nerve and ganglion cells. The discordance between MS and IHC measurements, together with the high degree of N-glycosylation suggests that the posttranslational modification interfered with recognition by the E1L3N antibody. We also found that samples B9, B17, B21, and B28 contained significant N192 PD-L1 glycosylation, but no PD-L1 was detected by IHC.Interestingly, the E1L3N antibody recognizes an intracellular, C-terminal PD-L1 epitope, whereas the glycosylated residue N192 is in the PD-L1 extracellular domain. Extracellular modification thus may alter an intracellular C-terminal PD-L1 epitope. Position N192 is not contained within the PD-1 recognition sequence, which includes residues between I54 and R125  or the rTargeted MS affords a systematic approach to develop assays for proteins for which high quality antibody reagents are unavailable. PD-L2 has been recognized as a regulator of PD-1 with higher affinity than PD-L1 , 26. HowThe immune-tumor interface is known to be regulated by at least a dozen other sets of protein switches, which can modulate PD-1/PD-L1/PD-L2 mediated signaling and provide independent regulatory signals . We seleTo explore the feasibility of measuring these proteins in melanomas, we used the LRP method for quantitative comparisons. The LRP approach does not require isotope labeled standards for quantitation, but can instead utilize other labeled peptide standards for signal normalization . PeptideFull development of a suite of several dozen SID MS assays for components of the tumor-immune interface is clearly feasible, particularly based on recent work by us , 36 and www.clinicaltrials.gov), such retrospective studies offer a tremendous opportunity to advance this field.The combination of MS analyses with IHC data could overcome limitations of IHC as the sole protein biomarker measurement platform in immunotherapeutic research and diagnostics. Moreover, a targeted MS platform to analyze multiple critical immune checkpoint and co-regulator proteins could address important, unresolved issues through retrospective analyses of well-annotated, archival specimens from completed immunotherapeutics clinical trials. For example, in trials of PD-1 inhibitors for melanoma, the KEYNOTE-001 trial (pembrolizumab)  and the ftp://massive.ucsd.edu/MSV000080433. Processed Skyline files can be downloaded at https://panoramaweb.org/labkey/Liebler_IO_checkpoints.url.Raw data files can be downloaded at:


GRN mutations and C9orf72 expansions showed a significantly increased frequency of Group 3 histopathology in the latter cases, suggesting more advanced cortical disease. Hence, we propose that IHC profiles of pTDP-43 and NeuN reflect the burden of pTDP-43 and its deleterious effects on neuron health.Frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP) is associated with the accumulation of pathological neuronal and glial intracytoplasmic inclusions as well as accompanying neuron loss. We explored if cortical neurons detected by NeuN decreased with increasing TDP-43 inclusion pathology in the postmortem brains of 63 patients with sporadic and familial FTLD-TDP. Semi-automated quantitative algorithms to quantify histology in tissue sections stained with antibodies specific for pathological or phosphorylated TDP-43 (pTDP-43) and NeuN were developed and validated in affected  and minimally affected (cerebellar cortex) brain regions of FTLD-TDP cases. Immunohistochemistry (IHC) for NeuN and other neuronal markers found numerous neurons lacking reactivity, suggesting NeuN may reflect neuron health rather than neuron loss in FTLD. We found three patterns of NeuN and pTDP-43 reactivity in our sample of cortical tissue representing three intracortical region-specific stages of FTLD-TDP progression: Group 1 showed low levels of pathological pTDP-43 and high levels NeuN, while Group 2 showed increased levels of pTDP-43, and Group 3 tissues were characterized by reduced staining for both pTDP-43 and NeuN. Comparison of non-C9orf72/GRN FTLD-TDP with cases linked to both The online version of this article (10.1186/s40478-017-0471-3) contains supplementary material, which is available to authorized users. C9orf72 expansions and mutations in the granulin precursor gene (GRN) [C9orf72 are typified by a hexanucleotide repeat expansion of GGGGCC in the first intron of the promoter region of the gene [C9orf72 dipeptide repeat peptides accumulate as TDP-43-negative but p62-positive neuronal cytoplasmic inclusions (NCI) in the cerebrum and cerebellum, but they rarely co-localize with TDP-43 inclusions [Frontotemporal lobar degeneration (FTLD) is the second most common cause of neurodegenerative dementia in patients younger than 65 , 50. Sevne (GRN) , 11, 21.the gene , 47. Impclusions , 49.GRN mutations; subtype B consists of moderate NCI’s and few DN’s throughout deep and superficial cortical layers and is associated with C9orf72 mutations; subtype C consists of few NCI’s and many long DN’s in superficial cortical layers; subtype D consists of moderate numbers of intra-nuclear NCI’s in the deep and superficial cortical layers and is associated with pathogenic mutations in the gene encoding the valosin-containing protein (VCP); and the recently described subtype E variant of FTLD-TDP consists of granulofilamentous NCI and dot-like neuropil aggregates throughout all cortical layers without any known associated mutations [C9orf72 mutation is the most common cause of familial FTD, FTD-ALS, and ALS [FTLD-TDP is a disorder characterized by diverse clinical, genetic, and pathological features , 42. Macutations , 28, 31.utations , 26. As utations . FTLD thutations , 57. Mor and ALS .In healthy neurons, nuclear TDP-43 co-localizes with NeuN, a neuron-specific protein in vertebrates involved in RNA splicing . IntenseFor all autopsy cases utilized, written informed consent was obtained from all patients using a protocol approved by the University of Pennsylvania Institutional Review Board in addition to post-mortem consent from next of kin. All postmortem brains were retrieved from the brain bank at the Center for Neurodegenerative Disease Research (CNDR) at the University of Pennsylvania . NeuropaGRN were screened by Sanger sequencing of the entire coding sequences of GRN and/or by targeted next generation sequencing (NGS) on a neurodegenerative disease-focused panel, MiND-Seq (Multi Neurodegenerative Disease Sequencing panel), which includes genes associated with FTD such as GRN, MAPT, VCP, CHMP2B, and SQSTM1 [C9orf72 hexanucleotide repeat expansion was tested with repeat-primed PCR and capillary electrophoresis as previously described [Genomic DNA was extracted from brain tissues using QIAamp DNA mini kit  following manufacturer recommendations. Mutations and variants in d SQSTM1 , 59. Sanescribed . The sizn = 7), superior temporal (n = 6), entorhinal (n = 1), anterior cingulate (n = 1), motor (n = 2), sensory (n = 5), angular (n = 1), and visual (n = 2) cortices. GRN cases were excluded from the analysis of cerebellar neuron health to compare C9orf72 cases and those without either the C9orf72 or GRN mutations (non-C9/GRN).A cohort with neuropathologically confirmed FTLD-TDP was selected from patients autopsied between 1987 and 2015  protein, HuC/HuD RNA binding proteins, neurofilament heavy chain (NEFH), and astrocytic glial fibrillary acidic protein (GFAP). From our cohort, we selected five random cerebral cortex tissue sections from each Group for this analysis, as well as four clinically and pathologically normal cerebral cortex tissue samples as normal controls (NC). Four randomly selected NC were also used for comparison to FTLD in the analysis of cerebellar neuron health.2 of pTDP-43 were re-stained at a higher concentration (1:150), and the most optimally stained tissue was included in our cohort. Digital images were obtained using a Lamina Multilabel slide scanner  with a 40× objective. The images had a pixel resolution of 0.2 μm/pixel, camera resolution of 2560 × 2160, and a bit depth of 16.Tissue sections were subjected to IHC and immunofluorescence (IF) using previously published protocols , 52. Bri2.Halo digital image software v2.0.1061.3  was used to develop detection algorithms to quantify pTDP-43 positive inclusions and NeuN staining. Specifically, the “Area Quantification” v1.0 setting (NeuN) and “CytoNuclear” v1.4 setting (TDP-43 inclusions and NeuN) were used to quantify NeuN reactive nuclei and TDP-43 inclusions, respectively. Previous work has validated the utility of these tools in detecting IHC-stained human tissue . For eac2 were then partitioned within the annotated region using the “tile portioning tool.” A random number generator selected which tiles to use for manual counts. Enough tiles were selected to represent at least 5% of the grey matter area of each tissue section. Manual counts of IHC positive profiles in selected tiles were aided by the “manual click counter” tool and followed by automatic counts that were completed by the algorithm. Visual inspection of all analyzed tissue was done to ensure the algorithms properly detected their targets. In the case of algorithm failure , small adjustments in OD were made to detect positive staining.Algorithm verification was done using tissue from our cohort. When defining algorithm parameters, all tissue were chosen at random and observers were blind to diagnostic information pertaining to the case. One out of six of the tissue sections analyzed here was used to validate each algorithm. After a random number generator was used to select regions for validation of these “CytoNuclear” algorithms, the grey matter of each tissue section was annotated using the “pen” tool. Tiles of 300-1500 μmSequential biochemical fractionation of human brain tissue was performed for four cases from our cohort , as previously described , 42. Bri2) of all tissue quantified was used as a cutoff for high TDP-43 pathology. The cutoff for high NeuN (~90 counts/mm2) was defined by visual inspection of clustering and validated by their “silhouette measure of cohesion and separation” (Si) which generated 0.389 as the mean Si value, representing a moderately cohesive cluster [Our primary interest here was to evaluate region-specific associations between NeuN and the pathologic burden of pTDP-43. ANOVA and Kruskall-Wallis tests using GraphPad software were applied to compare groups for normally and non-normally distributed data, respectively, followed by Tukey’s HSD test or Dunn’s test if significant . Normal . The correlation (ICC) between NeuN manual counts and automatic counts was 0.959. For pTDP-43 inclusions the ICC was 0.913. Furthermore, a Bland-Altman method was used to test agreement between the algorithm derived data and the manual counts by determining median bias and limits of agreement . For both algorithms, the majority of the measurements were within limits of agreement and the bias was quite small . Therefore, algorithm counts align well with those done manually. To ensure that variations in the sampled area of each tissue section did not influence the Groups that follow, we compared pTDP-43 and NeuN counts/mm2 to the area of analysis of each tissue section in our cohort using linear regression and found no linear correlation .Tissue sections from our cohort were stained for NeuN and pTDP-43 inclusions to develop the counting algorithms used in this study, and they serve as a relative index of NeuN level and TDP-43 pathology Fig. . Log-traFig. . The coent Fig. . For boC9orf72 expansions, 12 with GRN mutations and 34 non-C9/GRN cases. The cohort comprised 31 females and 32 males with a mean age at death of 68.8 years. Additionally, the mean brain weight was 1110.0 g. The pTDP-43 inclusions ranged from 0 to 308.8 counts/mm2, with a mean 28.9 counts/mm2. The range for NeuN staining was 0 counts/mm2 – 777.9 counts/mm2, with mean of 148.6 counts/mm2. Qualitatively, when a scatter plot of pTDP-43 pathology versus NeuN counts was generated and the mean pTDP-43 value was defined as a cutoff, three large Groups of subjects were observed .Counts for pTDP-43 inclusions and NeuN were obtained for our cohort’s cerebral cortex tissue Table . The cohved Fig. .Table 2, Additional file n = 87); Group 2 tissue sections showed a high burden of pTDP-43 inclusions and high level of nuclear NeuN positivity (n = 80); and Group 3 had a low burden of pTDP-43 inclusions and a low level of NeuN positive neuronal nuclei (n = 106). However, a small Group of 3 sections showed low NeuN and high pTDP-43 inclusion levels.We defined Groups 1-3 as described above based on NeuN nuclear staining and pTDP-43 inclusion densities  compared to Groups 1 (n = 1) and 2 (n = 1). As further confirmation, IHC was performed with additional neuronal markers . Additionally, we find that all tissue maintain Pan TDP-43 level, regardless of Group assignment ; Phase II consisted of the mid-frontal, anterior cingulate, entorhinal and superior temporal cortices (n = 161); Phase III consisted of the motor, sensory, and angular cortices (n = 65); and Phase IV consisted of the visual cortex (n = 23) (Table p = 0.0004). With an OR of 0.33 (95% CI 0.18-0.60), tissue in Phase I are 67% less likely than tissue in Phases III or IV to be in Groups 1 or 2 than Group 3. Likewise, tissue in Phases III or IV are 3.64 times more likely than tissue in Phase II to be in Groups 1 or 2 than 3 . There was no significant difference in Group number between Phases I and II (p = 0.6005).In bvFTD, due to underlying pTDP-43 pathology (bvFTLD-TDP), it was found that pTDP-43 inclusion deposits generally aggregate anteriorly to posteriorly in the CNS . 31 patiTo control for clinical phenotypic variation in TDP-43 regional pathology, we performed a subset analysis in 22 patients with bvFTD as well as 41 non-bvFTD patients and found a similar pattern , GRN mutation cases (n = 36), and non-C9/GRN cases (n = 104) using a GEE analysis, and found a significant difference (p = 0.0203)  less likely to be in Groups 1 or 2 than 3 compared to non-C9/GRN tissue. No significant difference was observed between C9orf72 and GRN tissue (p = 0.9269). To account for clinical phenotypic differences and region-specific associations, we performed sub-analyses of both bvFTLD-TDP patients and non-bvFTLD-TDP as well as all superior temporal cortex tissue—a region affected early in FTLD-TDP—and found similar results . However, they were unevenly distributed (p < 0.0001). Specifically, subtype A was comprised predominately of Group 3 tissue with fewer Group 1 or 2 tissue. Subtype B showed a similar, although much less pronounced trend, while subtype C was evenly distributed across all three Groups and subtype E was purely in Groups 1 and 2. Furthermore, we find that comorbidity has no effect on Group categorization. Of the 42 cases with comorbidities, 28.5% of tissue are in Group 1, 34.6% are in Group 2, and 36.9% are in Group 3. A 2-sided Fisher’s exact test does not find a significantly different distribution of Groups between cases with and without comorbidities (p = 0.177).All three Groups are found in FTLD-TDP subtypes A-C, yet Group 3 is not seen in subtype E Table . HoweveC9orf72expansions (C9FTLD-TDP) is the presence of dipeptide repeat inclusions in the cerebellum without the presence of TDP-43 pathology or overt neurodegeneration on postmortem examination, while neuroimaging studies find cerebellar atrophy of unclear significance [C9orf72 FTLD-TDP cases as well as four NC subjects were stained with NeuN to determine if there was a loss of NeuN IHC density in the granule cells between cases with C9orf72 expansion (n = 16) and those without (n = 7) .A unique signature of FTLD-TDP due to ificance , 40. Cer 7) Fig. , b. C9FTC9orf72 cases. Additionally, C9orf72 and GRN cases display a more advanced disease state, as defined by increased Group 3 frequency. Moreover, we found that Groups 1-3 can be used to model staging of the progression of pathology within an individual brain region and across brain regions.We investigated 63 FTLD-TDP cases and identified three Groups of histopathology that proceed from the aggregation of intracytoplasmic TDP-43 inclusions to progressive accumulation of TDP-43 inclusions followed by a reduction in these inclusions as well as reduced NeuN staining consistent with deteriorated neuron health. Indeed, in the cerebellar cortex, we find the granular layer neurons exhibit low NeuN staining in Utilization of a NeuN antibody was essential to this study. NeuN was discovered to be a product of the Fox-3 gene in 2011, which functions as a splicing activator for exon N30 of NMHC II-B via the intronic UGCAUG element in neurons , 13. In RBFOX3 (the gene encoding NeuN) knockout mice show decreased synapse activity and plasticity [Importantly, we show a reduction in other neuronal markers in adjacent sections stained with SFPQ and HuC/HuD Fig. . A 2015 asticity . Therefoasticity , 53, 60.C9orf72 expansions. Interestingly, research has shown that the granule cells of the cerebellum are marked by pTDP-43-negative but p62-positive NCI [C9orf72 cases accumulate in the cerebellum and could play a role neuron loss in these cells, though a direct causative link has not been shown [C9orf72 cases, and this is the first postmortem confirmation of this finding [Reduced NeuN staining also was observed in cerebellar granule cells of FTLD-TDP cases Fig.  with C9otive NCI . This suen shown . Notably finding , 34.The toxicity of pathologic TDP-43 is well established. First, past work has shown that the burden of cytoplasmic pTDP-43 expression correlated with neurotoxicity in cultured cells . In factStage 1- Very little pTDP-43 has been mislocalized to the cytoplasm and NeuN staining is similar to NC.Stage 2- Pathologic pTDP-43 aggregates have accumulated into inclusions, but they have yet to show NeuN loss., but we excluded small diffuse TDP-43 threads from our analysis in order to improve the algorithm’s reliability. Since these pTDP-43 positive neuritic lesions are abundant in FTLD-TDP subtypes A and E, this strategy may have artificially decreased the frequency of Group 2 in these subtypes. Likewise, separate pTDP-43 quantification algorithms were not developed specifically for each subtype. Still, we find that Group 2 is well represented in both subtypes A and E  that FTLD-TDP cases due to C9orf72 and GRN mutations were more common in Group 3 than Groups 1 or 2. This implies that these cases have a more severe disease phenotype compared to non-C9/GRN FTLD, a hypothesis substantiated by previous studies which showed increased rates of decline in C9orf72 cases and greater brain atrophy in GRN cases [C9orf72 [GRN mutations displayed greater atrophy of the frontal, temporal, and parietal cortices [C9orf72 is not consistent in the literature. A study of Australian FTLD cases finds lessened atrophy and slower disease progression in C9orf72 [C9orf72 methylation state, which has been shown to affect age of onset and neuron loss [Moreover, our data suggest more severe neurodegeneration in cases with the nd Table  that FTRN cases , 33, 58.[C9orf72 , 30, 33.cortices , 58. Yet C9orf72 . Howeverron loss , 36, 48.In addition to modeling intracortical region-specific staging of disease, we investigate the progression of pathology within an individual across brain regions Fig. . In bvFT


TDP-43 proteinopathy is a prominent pathological feature that occurs in a number of human diseases including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and inclusion body myositis (IBM). Our recent finding that TDP-43 represses nonconserved cryptic exons led us to ask whether cell type-specific cryptic exons could exist to impact unique molecular pathways in brain or muscle.In the present work, we investigated TDP-43’s function in various mouse tissues to model disease pathogenesis. We generated mice to conditionally delete TDP-43 in excitatory neurons or skeletal myocytes and identified the cell type-specific cryptic exons associated with TDP-43 loss of function.Comparative analysis of nonconserved cryptic exons in various mouse cell types revealed that only some cryptic exons were common amongst stem cells, neurons, and myocytes; the majority of these nonconserved cryptic exons were cell type-specific.Our results suggest that in human disease, TDP-43 loss of function may impair cell type-specific pathways.The online version of this article (doi:10.1186/s13024-016-0144-x) contains supplementary material, which is available to authorized users. TARDBP) [Recent genetic evidence has established the linkage between the neurological disorders amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) –5. The kTARDBP) . Since tTARDBP) –12. Of pTARDBP) , 14. To in vitro inducible stem cell model of TDP-43 deletion. However, we have yet to establish the cell type-specific cryptic exons that arise in vivo. Here, we generated conditional Tdp-43 knockout mice to specifically delete Tdp-43 in excitatory neurons and skeletal myocytes. We found that Tdp-43 cryptic exons are highly variable between cell types and that many distinct pathways are altered—novel findings that have mechanistic and therapeutic implications for human diseases exhibiting TDP-43 proteinopathy.We have recently found that TDP-43 plays a major role in repressing nonconserved cryptic exons . These cTardbp knockout mice (TardbpF/+) with CamKIIa-Cre transgenic mice to obtain a cohort of CamKIIa-Cre;TardbpF/+ mice which were subsequently crossbred to TardbpF/+ mice to generate the final cohort: CamKIIa-Cre;Tardbp+/+, CamKIIa-Cre;TardbpF/+ and CamKIIa-Cre;TardbpF/F mice. A similar strategy was applied when crossbreeding the MLC-Cre driver line to TardbpF/+ mice. All mouse experiments were approved by the Johns Hopkins University Animal Care and Use Committee.We crossbred our conditional CamKIIa-Cre line, wildtype and floxed mice were anaesthetized and perfused with 4% paraformaldehyde. Brains were embedded into paraffin, cut into 10 μm sections and stained according to standard protocols. For the MLC-Cre line, wildtype and floxed mice were anaesthetized and sacrificed by decapitation. Muscle tissue was then rapidly dissected and flash frozen in liquid nitrogen cooled isopentane. Frozen cryosections were cut at 10 μm thickness and stained according to standard protocols. Immunoreactivity was visualized using the Vectastain ABC Kit and diaminobenzidine peroxidase substrate (Vector Laboratories). Images were obtained using Olyumpus BX53 microscope.For the CamKIIa-Cre line, wildtype and floxed mice were anaesthetized and sacrificed by decapitation. Brain tissue was then rapidly dissected and manually homogenized in RIPA buffer (Sigma) containing an EDTA-free protease inhibitor cocktail (Thermo Scientific). For the MLC-Cre line, wildtype and floxed mice were also anaesthetized and sacrificed by decapitation. Muscle tissue was snap frozen in isopentane cooled with liquid nitrogen, manually ground into a powder, and then homogenized in RIPA buffer with protease inhibitor cocktail. Protein concentration was determined using the BCA assay (Pierce). Proteins were resolved using the NuPAGE 4-12% Bis-Tris Gel (Novex) with NuPAGE MES SDS Running Buffer (Novex), and transferred to PVDF membrane (Millipore) with NuPAGE Transfer Buffer (Invitrogen).For the The following antibodies were used for protein blots, immunofluorescence, and immunohistochemical analyses: rabbit anti-TDP-43 (Proteintech 10782-2-AP and 12892-1-AP), anti-NeuN monoclonal antibody (Chemicon), anti-GAPDH monoclonal antibody (Sigma), Alexa Fluor 488-conjugated Donkey anti-Guinea Pig IgG (H + L) antibody (Jackson ImmunoResearch), Alexa Fluor 594- and 647-conjugated Donkey anti-goat and anti-rabbit IgG (H + L) antibodies (Life Tech.).CamKIIa-Cre;TardbpF/F  and littermate control mice  using TRIzol (Life Tech.) and RNeasy Mini kits (Qiagen). Total RNA from 2 month old male MLC-Cre;TardbpF/F  and littermate control mice  was also extracted in a similar manner. For the CamKIIa-Cre line, 3 control brains and 3 knockout brains were analyzed and all mice were female. For the MLC-Cre line, 2 control quadriceps and 2 knockout quadriceps were analyzed and all mice were male. 100-bp paired end RNA-seq libraries were generated using Illumina Tru-seq kits and then sequenced on an Illumina HiSeq 2000. For RT-PCR analysis, total RNA was isolated using RNeasy Mini Kit (Qiagen). cDNA was synthetized using RevertAid First Strand cDNA Synthesis Kit (Thermo Scientific) with random primers. RNA-seq analysis was performed using HISAT [Total RNA was extracted from hippocampi of 3 month old female ng HISAT  and Cuffng HISAT  softwareng HISAT . Crypticng HISAT . To idenng HISAT .Tardbp knockout alleles [CaMKIIα-Cre [MLC-Cre [CaMKIIα) drives expression primarily in the excitatory neurons of the cortex and hippocampus whereas the promoter of the myosin light chain 1/3 locus (MLC) drives expression in type II fast-twitch skeletal muscle fibers. Efficient deletion of Tdp-43 can be detected by immunoblot in brain .To identify the cryptic exons of mouse neurons, RNA-sequencing (RNA-seq) analysis was performed using RNA extracted from hippocampi of 3 month old deletion , we alsoice Fig. . Neuron-ice Fig.  and coulice Fig. -e.Fig. MLC-Cre;TardbpF/F knockout mice and controls. Indeed, numerous muscle-specific cryptic exons could be identified . For example, the cryptic exon in Ube2d1 is highly incorporated in stem cells, moderately incorporated in myocytes, and absent in neurons  do not induce nonsense mediated decay, but still have an impact on protein structure. These cryptic exons do not contain any stop codons and have sequence lengths that are multiples of three, thereby preventing detrimental frameshifts  will be difficult to envision due to the sizeable number of nonconserved cryptic exons per cell. Furthermore, because nonconserved cryptic exons are different between mouse and human, testing splicing modulators for human cryptic exons in animal models is essentially impossible. However, the general splicing repression function of TDP-43 is conserved. Thus, it may be possible to use mouse models of TDP-43 deletion to specifically test therapeutic strategies that rescue TDP-43 mechanism of action rather than directly targeting individual cryptic exons. One strategy would employ gene therapy to introduce designer splicing factors—chimeric proteins that would couple the UG binding domain of TDP-43 with non-aggregating splicing repressor domains —into neuIf neuron loss or skeletal muscle degeneration can be attenuated, such a therapeutic strategy could be rapidly translated into the clinic. Moreover, the observation that cryptic exons can occasionally introduce inframe insertions into mRNA suggests that certain human TDP-43 cryptic exons could represent biomarkers for human disease. We envision the development of specific antibodies to detect neoantigens introduced by human inframe cryptic exons in CSF or blood from patients, serving as either diagnostic biomarkers or tools to monitor the efficacy of treatments in future clinical trials.This study demonstrates that Tdp-43 represses a unique set of cryptic exons, depending on cellular context. Thus, the pathways impacted by Tdp-43 loss-of-function and cryptic exon incorporation are likely distinct for each cell type. These results have important implications for human disease, given that Tdp-43 proteinopathy can manifest in various tissues.


Flexible porous graphene array offers a minimally invasive but high efficiency neuromodulation scheme with potential applications in cortical mapping, brain-computer interfaces, treatment of neurological disorders, where high resolution and simultaneous recording and stimulation of neural activity are crucial.Neural sensing and stimulation have been the backbone of neuroscience research, brain-machine interfaces and clinical neuromodulation therapies for decades. To-date, most of the neural stimulation systems have relied on sharp metal microelectrodes with poor electrochemical properties that induce extensive damage to the tissue and significantly degrade the long-term stability of implantable systems. Here, we demonstrate a flexible cortical microelectrode array based on porous graphene, which is capable of efficient electrophysiological sensing and stimulation from the brain surface, without penetrating into the tissue. Porous graphene electrodes show superior impedance and charge injection characteristics making them ideal for high efficiency cortical sensing and stimulation. They exhibit no physical delamination or degradation even after 1 million biphasic stimulation cycles, confirming high endurance. In  Intracranial recording and stimulation have played critically important roles in studying basic neural processes underlying human behavior and causes of neurological disorders1389101011314152 2122242O5272823An ideal cortical microelectrode array for neural recording and stimulation needs to be minimally invasive, flexible and robust, while providing low impedance and high charge transfer capacity. Conventional neural electrodes are made of noble metals and alloys, with platinum electrodes being the most typical ones in clinical use171819in vivo experiments with rodents that low impedance of porous graphene microelectrodes allows recording of low-amplitude evoked potentials from the rat’s somatosensory cortex with high signal-to-noise ratio. High efficiency cortical stimulation in the motor cortex has been shown to evoke transient ankle and knee flexion using same exact arrays in consecutive recording and stimulation experiments.Graphene has recently become a desirable material for neural applications owing to superior properties such as high conductivity303130303035383940412 laser, which is about 130 μm, and the resolution of the software that drives the laser head, direct laser pyrolysis provides porous graphene spots of 250 μm or larger side length with acceptable consistency and uniformity for the lithography afterward. As for patterning smaller structures, an indirect approach with a shadow mask during pyrolysis was also investigated, as shown in 43We fabricated porous graphene arrays using the process flow shown in 2 laser machining system. Besides being flexible, the polyimide substrate provides mechanical support to the porous graphene layer. During pyrolysis on polyimide films, localized temperatures rises over 2500 °C, which breaks the C─C, C=O and N─C bonds, as confirmed by the dramatically decreased oxygen and nitrogen contents. Then aromatic compounds rearrange to form graphene structures−1, the 2D peak at 2700 cm−1, and the D peak at 1350 cm−1, are observed. The D peak represents defects or bent sp2 carbon bonds. The increase in laser power results in a decrease in D peak initially and a subsequent increase with power beyond 5.5 W, as shown by a minimum in the intensity ratio of D and G peaks in Porous graphene in various dimensions and geometries can be simply patterned on polyimide substrates using a computer-controlled COmc) and most positive (Ema) voltages across the electrode/electrolyte interface. Maximum polarization is reached when either Emc or Ema exceeds the water window. mc and Ema reaching −0.98 V and 0.8 V, respectively. The injection current was 4.4 mA. 2 to 3.1 mC/cm2. High CIC results were consistent across many samples fabricated at different batches (c) and CIC for neural electrodes made of various materials. Coating layers, such as iridium oxide, poly (PEDOT) and carbon nanotubes, have been employed for increasing the electrodes’ surface area and hence charge transfer capability. However, mechanical failures due to cracking and delamination pose a threat to the surrounding tissue, limiting their use for long-term chronic studies or implantable medical systems172 and 3 mC/cm2 CIC for delamination of iridium oxide has been shown in in vivo experimentsin vivo cortical stimulations, with current injections as high as 3.1 mC/cm2. However, no change in impedance or physical appearance of the electrodes was observed. Furthermore, SEM inspections of the porous graphene electrodes after soaking in PBS solution for 30 days show no obvious delamination or physical degradation compared to an unused electrode . The impedance of a porous graphene electrode (Sample #1) was found to be approximately two orders of magnitude smaller than a similar-size Au electrode. Chemical doping further decreased the impedance, resulting in an impedance of 519 Ω at 1 kHz, as shown in  batches . Table Slectrode . MechaniIn vivo neural recording experiments were performed on adult rat models. An anaesthetized rat was placed with its head fixed in a stereotaxic apparatus. A craniotomy exposed 4 mm × 4 mm region of right barrel cortex. A 16-electrode array was placed on the exposed cortical surface, as shown in Field potentials at the pial surface of barrel cortex in the anesthetized rat were recorded showing spontaneous up and down states cross the 16-electrode array, as shown in in vivo cortical stimulation experiments, currents lower than 1.25 mA correspond to k parameters below 1.85, while achieving successful ankle and knee flexion control. Previous experimental studies have also shown that no tissue damage would be induced by small surface electrodes (areas less than 0.01 cm2) as long as stimulation is performed within the Shannon limit for k = 1.85After recording physiological oscillations and evoked potentials, the next step was to investigate cortical microstimulation with porous graphene arrays. Using an array placed over motor cortex this time, stimulus trains were applied to a rat animal model to evoke transient ankle and knee flexion in the contralateral leg, as illustrated in In summary, the flexible porous graphene electrode arrays presented in this paper could be a powerful tool for neuroscience research, particularly for electrical microstimulation, and high density spatio-temporal cortical mapping applications. High CIC and lack of delamination and degradation for porous graphene electrodes can open up new avenues for brain computer interfaces based on minimally invasive cortical stimulation. The elimination of depth electrodes could improve the efficiency of clinical treatments, such as deep brain stimulation for Parkinson’s and responsive neuro-stimulation for epilepsy.2 laser with wavelength at 10.6 μm was adopted.A laser engraving and cutting system  was used for irradiating polyimide films . CORaman spectra of the porous graphene were taken by NTEGRA Spectra (NT-MDT Co.) system with a 532-nm laser excitation source.After the patterning of porous graphene, the polyimide film was cleaned with acetone, isopropyl alcohol, and deionized water, followed by de-moisturizing on a hotplate at 150 °C for 5 minutes. Then the polyimide film was attached to a 4 inch Si wafer spin-coated with polydimethylsiloxane (PDMS), which is helpful to maintain the film flat during all following processes. Cr/Au (10 nm/100 nm) layers were deposited with electron-beam evaporation, and the metal wires and contact pads were patterned with S1818 photoresist and wet etching. 9 μm thick SU8-2007 was spin-coated and patterned for encapsulation. Electrode openings were 250 μm × 250 μm. Doping in nitric acid (70%) for 30 seconds helped to decrease the impedance of the electrodes.c is calculated from the time integral of the cathodic current of the CV within the water electrolysis window and divided by the geometry surface area of the electrode. CIC is calculated from the current pulse divided by the geometry surface area of the electrode.The Gamry Reference 600 potentiostat was connected in the standard three-electrode configuration in 0.01 M PBS solution. The counter electrode was Pt and the noncurrent-carrying reference electrode was Ag/AgCl. EIS measurements were taken between 0.1 Hz to 300 kHz using 10 mV RMS AC voltage. For CV tests, the potential of the working electrode swept three times across the water window at the scan rate of 100 mV/s. In choronopotentometry measurements, three successive identical biphasic current pulses were applied after stabilization of the system, and the simultaneous voltage transient was recorded. CSCExperiment procedures were approved by the Institutional Care and Use Committee of the University of Pennsylvania. Two rats were used. Each rat was anesthetized with a ketamine (60 mg/kg), dexdomitor (0.25 mg/kg) solution and placed in a stereotaxic frame. The ketamine-dexdomitor solution, at the concentrations we used in the experiments, put the animal at a surgical plane of anesthesia , as required for doing a craniotomy. Craniotomy was performed to expose the right barrel cortex (recording experiments) or motor cortex (stimulation experiment). A skull screw was placed in the left frontal bone to serve as the reference electrode for the recordings. The array was placed on the exposed cortical surface. For recording evoked activities, a pair of needles was used to electrically stimulate the left mystacial pad. Wide-band (0.35–7500 Hz) evoked and spontaneous cortical activity was recorded at 25 kS/s .How to cite this article: Lu, Y. et al. Flexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing. Sci. Rep.6, 33526; doi: 10.1038/srep33526 (2016).


The composition of gut bacterial communities changed in a similar manner over time towards a common decay community. OTUs belonging to Bacteroidales  significantly declined while Clostridiales  and the fly-associated Gammaproteobacteria Ignatzschineria and Wohlfahrtiimonas increased. Our examination of human caeca microflora in decomposing cadavers adds to the growing literature on postmortem microbial communities, which will ultimately contribute to a better understanding of decomposition processes.The human microbiome has demonstrated an importance for the health and functioning in living individuals. However, the fate of the microbiome after death is less understood. In addition to a better understanding of microbe-mediated decomposition processes, postmortem succession of human-associated microbial communities has been suggested as a possible forensic tool for estimating time since death, or postmortem interval (PMI). The objective of our study was to document postmortem changes in human gut bacterial communities. Gut microflora were repeatedly sampled from the caeca of cadavers as they decayed under natural environmental conditions. 16S rRNA gene amplicon sequencing revealed that over time, bacterial richness significantly increased ( Decomposition of vertebrate mortalities is driven in part by microbial activity. Following death, a lack of oxygen in the body results in cell autolysis, releasing macromolecules. The body’s resident microbes, particularly those concentrated in the gastrointestinal tract, metabolize these cellular products in the process of putrefaction. The fermentative activities of these microbes cause bloating as gasses build up inside the carcass, and ultimately liquefaction of tissues . While iUnderstanding the processes and dynamics of decomposition has application in forensic science, particularly with respect to developing robust estimates of time since death, or postmortem interval (PMI). All methods have limitations, thus using a combination of approaches typically provides the best estimates of PMI . TherefoBacteroides and Lactobacillus declined exponentially as decay progressed. This suggested that the microbial communities changed in structure over time, and led to the hypothesis that other populations of bacteria may be useful as biomarkers of time since death. Our previous study was limited to examining only three microbial populations using targeted qPCR. Therefore, the objective of this study was to characterize and quantify the entire bacterial community of the human gut following death as decomposition progresses. We hypothesized the communities would change in structure with time, with a decline in Bacteroidetes, and increase in more robust taxa such as Clostridia and Proteobacteria. The changes in intestinal microflora have been examined in mice up to 48 h postmortem ; a habitat not previously investigated using high throughput sequencing (to our knowledge). In a previous study, we sampled gut microflora of the caeca of six deceased human subjects repeatedly following death, until tissues were too compromised to distinguish . Using qstmortem . Here wehttp://web.utk.edu/ fac/collection.html). As no living human subjects were involved, this work was exempt from review by the University of Tennessee Institutional Review Board. No preference was employed for sex, age, ancestry, weight, etc. FAC standard protocol for accepting donors ensured the individuals did not have communicable diseases. The bodies were not autopsied or embalmed; they were immediately refrigerated after death and placed at the ARF within three days. The four individuals  ranged in age at death from 62 to 67 years and weights from 56 to 77 kg, and all died of natural causes. A small incision was made in the abdomen and sterile swabs were used to collect gut material from the caecum. The incision was sealed with tape and re-sampled daily until tissues were too decayed to identify. Sampling times were converted to cumulative degree hours (CDH) based on hourly measurements of air temperature from a local meteorological station as previously described  in the summer of 2011, as part of a larger study described previously . The indescribed . Since aescribed .SRP098575).DNA was extracted using a MoBio PowerSoil DNA extraction kit. 16S rRNA gene libraries (V4 region) were built and sequenced on the Illumina MiSeq platform at the Hudson Alpha Genomic Service Lab  using primers and conditions described in T test. Nonmetric multidimensional scaling on Bray–Curtis distances was performed to visualize community similarities and differences.Prior to alpha-diversity calculations, libraries were subsampled to 25,082 reads per library . Alpha diversity statistics were calculated in Mothur v.1.37.0, and included Good’s coverage estimate, richness (number of OTUs), Simpson’s Diversity index. Beta diversity analyses were done in Primer v6 . OTU cours) between the top 30 most abundant OTUs (with relative abundances >  0.3) and postmortem time were calculated in R with a Bonferroni adjustment for multiple comparisons (adjusted α < 0.0016)  routine in Primer, using a one way design on the calculated Bray–Curtis similarities, to determine the contribution of each OTU to the dissimilarity between early and late groups and identify the taxa that contribute the most to the observed patterns . Non-par 0.0016) .The sampling method, which involved introduction of a sterile swab into the abdominal cavity, undoubtedly introduced some oxygen to the gut, which would have normally been anaerobic. We attempted to limit this introduction as much as possible and included several bodies as controls to determine if the sampling had an effect. The method and controls are discussed in our previous study . The sixAfter processing to remove erroneous sequences, 8,756,105 sequences remained in our dataset. The sample with the least number of sequences contained 25,082, so all other samples were randomly subsampled to this size. At 25,082 sequences per sample, mean Good’s coverage for all samples was 0.998. Replicate libraries were made for a random selection of four samples to assess technical error. Duplicates were more similar to each other than to other libraries, with Bray–Curtis similarities of community composition ranging from 92.06 to 93.52 at the OTU level and 97.55 to 98.77 at the phylum level. Initial screening of the sequence libraries revealed that one individual (A6), which had a percutaneous endoscopic gastrostomy (feeding) tube prior to death, had very different starting postmortem gut microbial communities compared to the other three . The comrs) = 0.449, p = 0.003). In contrast, diversity (Simpson’s Index) was significantly inversely correlated to time  .Over time, the taxon richness of the bacterial communities increased, while the diversity significantly decreased, indicating a decrease in evenness . The num< 0.001) . An NMDS< 0.001) . Over th< 0.001) . This sh1) sensu around tBacteroides and Parabacteroides (Phylum: Bacteroidetes), and the Firmicutes Faecalibacterium, Phascolarctobacterium, Blautia, Lachnospiraceae incertae sedis.The ‘early’ microbial communities had a mean of 135 ± 17 OTUs. The diversity was high, with a mean inverse Simpson’s Index of 12.93 ± 3.91. They had an average Bray–Curtis similarity of 59.42%. Major phyla in these communities were Firmicutes and Bacteroidetes,characteristic of human gut communities . A SIMPET test, t =  − 3.215, p = 0.003). These late microbial communities were also more variable compared to the early microbial communities, with a mean Bray–Curtis similarity of 49.45%. The inverse of the Simpson’s Diversity Index was 6.608 ± 3.78, indicating significantly lower diversity than the early communities . Firmicutes still dominated, but we observed reduced relative abundances of Bacteroidetes at the phylum level , and Gammaproteobacteria OTUs   .F = 6.992, p = 0.001), largely due to the proliferation of Proteobacteria and increase in Ignatzschineria , we examined the relationships between OTUs and CDH. In this study we documented the shifts in human gut microflora postmortem, as deceased human subjects decayed in an outdoor environment. While other studies of postmortem human microbial communities have included fecal or rectal sampling e.g., , here weOver time, the bacterial communities exhibited decreased diversity. As richness was not affected, this indicates a reduction of evenness, as the communities become dominated by a few dominant genera. This is typical of a disturbance response or a bloom event. In a decomposing body, likely both scenarios occurred: the rapidly shifting environmental conditions and production of putrefaction products likely stressed some members of the community, while others were more tolerant and proliferated on the newly available substrates. It was notable the variation between individuals increased in the late communities; that is, bacterial communities were more similar between the three individuals in the beginning. External factors such as temperature, soils, and arthropod communities were relatively similar between the individuals, as they were all placed in the same environment around the same time. However, internal differences that we could not control for  may have influenced the trajectory of the decomposer communities. For example, individual A6 had a remarkably different starting microbiome, and exhibited an altered decomposition trajectory from the other three . It should also be recognized that decomposition, because of its highly dynamic nature, is not entirely deterministic and would be subject to stochasticity that would result in slightly different trajectories of the bacterial communities between individuals. Other studies of microbial community succession have shown that the relative importance of stochastic and deterministic  processes is generally time dependent, with stochastic processes dominating early in succession, and deterministic processes becoming more important later on .Clostridium spp. are normal members of the human gut microflora, and have been reported as a prominent members of postmortem microbial communities, including both internal organs and external sites    and blowhagidae) . Wohlfahy larvae . Thus, iy larvae ; this raBacteroides and Parabacteroides, which declined over time and were significantly inversely correlated to PMI. This corroborates our previous study with six individuals, in which we quantified Bacteroides using qPCR and demonstrated a significant, quantifiable decay relationship in the relative abundances of these organisms with increasing PMI . While our sample size is very small, these analyses revealed taxa related to PMI. These taxa include sing PMI . ClostriOur examination of human gut microflora of the caecum in decomposing human subjects adds to the growing literature on postmortem microbial communities. While the small sample size used here limits the interpretation, and would need to be validated by further study, it has provided new insight into postmortem patterns of microbial succession, and thus may contribute to our overall understanding of decomposition processes.10.7717/peerj.3437/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.3437/supp-2Supplemental Information 2Mothur code for sequence processingClick here for additional data file.