Use of stable water isotopes has become increasingly popular in quantifying water flow paths and travel times in hydrological systems using tracer‐aided modeling. In snow‐influenced catchments, snowmelt produces a traceable isotopic signal, which differs from original snowfall isotopic composition because of isotopic fractionation in the snowpack. These fractionation processes in snow are relatively well understood, but representing their spatiotemporal variability in tracer‐aided studies remains a challenge. We present a novel, parsimonious modeling method to account for the snowpack isotope fractionation and estimate isotope ratios in snowmelt water in a fully spatially distributed manner. Our model introduces two calibration parameters that alone account for the isotopic fractionation caused by sublimation from interception and ground snow storage, and snowmelt fractionation progressively enriching the snowmelt runoff. The isotope routines are linked to a generic process‐based snow interception‐accumulation‐melt model facilitating simulation of spatially distributed snowmelt runoff. We use a synthetic modeling experiment to demonstrate the functionality of the model algorithms in different landscape locations and under different canopy characteristics. We also provide a proof‐of‐concept model test and successfully reproduce isotopic ratios in snowmelt runoff sampled with snowmelt lysimeters in two long‐term experimental catchment with contrasting winter conditions. To our knowledge, the method is the first such tool to allow estimation of the spatially distributed nature of isotopic fractionation in snowpacks and the resulting isotope ratios in snowmelt runoff. The method can thus provide a useful tool for tracer‐aided modeling to better understand the integrated nature of flow, mixing, and transport processes in snow‐influenced catchments. We present a novel modeling method for snowpack isotope fractionation to estimate spatiotemporal variability of isotope ratios in snowmeltOur parsimonious model uses two calibration parameters that alone account for the isotopic fractionation caused by snow sublimation and meltWe provide a modeling experiment to demonstrate the model functionality and a proof‐of‐concept comparison using snowmelt isotope data During freeze/thaw, the bulk isotopic content of the snowpack does not change, but water with different isotopic signatures is redistributed and thereby, the isotopic stratigraphy of snow layers is somewhat altered from the original snowfall [r et al. . They foClaassen and Downey, Taylor et al., Feng et al., Fekete et al., Smith et al., both space and time that would account for the isotopic fractionation processes in snowpacks, even though the need for such methods is evident for hydrograph separation or tracer‐aided modeling studies in snow‐influenced regions [Stadnyk et al., Dahlke and Lyon, Dietermann and Weiler, Schmieder et al., Previous work [The motivation of this study was to produce a spatiotemporally consistent estimate of the isotope composition of snowmelt, which can subsequently serve as input for tracer‐aided studies in snow‐influenced environments. For this purpose, we developed spatially and temporally distributed, but still parsimonious, model to simulate (1) the isotopic enrichment of snowpack due to sublimation and (2) time‐dependent depletion of snowmelt isotopic signal. Our snow isotope simulations are coupled with a spatially distributed process‐based snowmelt and accumulation model providing, for the first time, a tool to estimate quantitatively the fully spatially distributed isotopic signals of snowmelt water at the catchment scale. Our isotope modeling approach is truly parsimonious having only two parameters to account for isotope fractionation caused by sublimation and snowmelt.The paper is structured as follows: in section 2Karssenberg et al., Our new simulation approach combines a process‐based snow accumulation/melt model with parsimonious calculation routines to simulate the isotopic evolution of the snowpack and snowmelt runoff. The model calculations are fully spatially distributed in grid cells using the PCRASTER PYTHON framework [Wigmosta et al. [Walter et al. [Anderson, f (MJ kg−1) is the latent heat of fusion; ρw (kg m−3), density of water; ΔSWE (m), change in snow water equivalent; Rnet (MJ m−2), net shortwave radiation; Lnet (MJ m−2), the net longwave radiation; Qs (MJ m−2), sensible heat exchange; QL (MJ m−2), latent heat of vaporization or condensation at the snow surface; QP (MJ m−2), advective heat from rainfall; Ci (MJ kg−1 °C−1), specific heat capacity of ice; ΔTsn (°C) is the change in snow temperature. The short and longwave radiation terms are adjusted for canopy sheltering and hillshading according to Wigmosta et al. [ESRI [Calculation of the spatially distributed process‐based snow module relies primarily on the methodology provided by a et al.  and Waltr et al. , buildina et al.  and ESRIl. [ESRI   is solved using the mass balance equation:j is the simulation time step; SWE (mm), snow water equivalent in the snowpack; iP (‰), isotope ratio in the precipitation; Sthru (mm), throughfall bypassing interception storage (equation (S33)); Pliq (mm), liquid precipitation (equation (S6)); iint (‰), isotope ratio of snow interception storage; Sunl (mm), water unloaded from interception storage (equation (S34)); isnowE (‰), isotope ratio of sublimated water from equation Esnow (mm), amount of simulated snow sublimation (equation (S29)); imelt (‰), isotope ratio of snowmelt from equation Smelt (mm) is the amount of snowmelt (equation (S28)). Isotope ratios are presented using the δ‐notation in reference to Vienna Standard Mean Ocean Water standards.Snow sublimation isotopically enriches the snowpack. This is achieved by introducing an offset parameter to determine the level of depletion of the sublimated water relative to the snowpack:isnowE (‰) is the isotope ratio of the sublimated water from snow; isn (‰), isotopic concentration of the snowpack; and Efrac (‰) is the offset parameter. Efrac is a calibration parameter and is allowed to take values between 0 and 15‰ based on the equilibrium difference of 15‰ between ice and vapor isotopic ratio at 0°C temperatures [Ellehoj et al., Efrac parameter.Mfrac assigning a more depleted value for the initial snowmelt, and tracking the number of days with simulated snowmelt dmelt runoff to reduce the offset over time:imelt (‰) is the isotope ratio of the snowmelt water; Mfrac (‰), offset parameter; and dmelt is the number of days snowpack has experienced snowmelt. Mfrac is a calibration parameter taking values between 0 and 3.5‰ based on the equilibrium difference of 3.5‰ between ice and liquid water isotopic ratio [Gat and Gonfiantini, dmelt ≥ 1, are used: (i) SWE > 10 mm, with the analogy that the snowpack needs to be sufficiently deep to allow contact time between ice and water leading to isotopic fractionation, (ii) the snowmelt runoff flux need to exceed a threshold of 2 mm d−1, with the aim to simulate the evolution of snowmelt primarily during the overall melt and to ignore minor melt events in the beginning and middle of the snow covered period. If these conditions are met, the parameter dmelt is cumulatively increased by one for each melt day, leading to a progressively lower difference between isotopic composition of snowmelt and the remaining snowpack.The onset of overall snowmelt is isotopically depleted with respect to the average snowpack, and the difference reduces over time. This is achieved by using an offset parameter iint (‰) is solved fromIsn (m) is the interception storage and intEi (m) is the isotopic composition of water sublimated from the interception storage with the sublimation fractionation offset parameter Efrac included as in equation Eint is approximated from latent heat exchange with the same equations as for ground snowpack (equations (S20)–(S23) and (S29)), except the snow temperature (Ts) in the interception storage is assumed to equal air temperature aT and the measured wind speed W is used instead of wind speed Wcan reduced by canopy effects (equation (S3)).The isotopic composition of interception storage 3To demonstrate functionality of the model outlined above, we used data from three long‐term experimental catchments Figure : BruntlaThe Bruntland Burn catchment was only used as a platform for a synthetic modeling experiment to demonstrate how the model functions in simulating spatiotemporally distributed snow sublimation and melt as well as the isotopic transformations involved. The modeling experiment was driven by averaged climate data from the Krycklan catchment. The modeling experiment setup along with its results and discussion are presented in section Krycklan and Bogus catchments were further used to test the model output against field data of snowmelt runoff collected with snowmelt lysimeters. The details for the model calibration at the sites with the modeling results and discussion are presented in section Here we briefly describe the relevant topographic, climatic, and canopy characteristics that influence snow accumulation and melt at the catchments used in empirically based model testing (Krycklan and Bogus). We also explain the climatic data used to drive the simulations and snowmelt lysimeter data used in model calibration and testing. For a more comprehensive description of the catchments, the reader is referred to the work cited below.3.12), located in the Swedish boreal forest  with a part of the catchment covered by a canopy‐free minerogenic mire (18%) dominated by Sphagnum moss.The Krycklan catchment , spruce forest (closed canopy), and open area (Table S2 in supporting information S1). Location of open and closed canopy lysimeters is given in Figure Peralta‐Tapia et al. [Snow water equivalent (SWE) in Krycklan was measured starting every midwinter and repeated at approximately 2–3 week intervals until the snow had melted [a et al. .3.22) in the Dry Creek experimental watershed (DCEW) where a V‐shaped fluvial valley slopes steeply from 1684 to 2135 m asl. Several field and simulation studies in the wider DCEW have focused on understanding the spatially varying snow distribution and melt processes [Kelleners et al., Homan et al., Eiriksson et al., Kormos et al., Evans et al., Prunus spp. and Ceanothus spp.) cover the most of the catchment, with a small fraction of taller tree canopies (Pseudotsuga menziesii and Pinus ponderosa) focused primarily in the valley bottom near the stream.The Bogus catchment is a small headwater  to build a linear regression model to estimate continuous a time series for precipitation from daily T similarly as in a et al. . In addiNational Climatic Data Center, Kormos [SWE data for Bogus were acquired from the SNOTEL  station where SWE is measured continuously with a pressure transducer [, Kormos .44.1Carey and Quinton, Varhola et al., Koeniger et al., Dahlke and Lyon, Schmieder et al., To demonstrate how the model functions in simulating spatiotemporally distributed snow sublimation and melt as well as the isotopic transformations involved, we devised a synthetic simulation based on a “thought experiment.” The aim of the exercise was to highlight how our simulations take into account different landscape position  and canopy cover—both shown to be potentially influential for snow accumulation and melt [2 catchment in the Scottish Highlands [Soulsby et al., Laudon et al., Laudon et al., Peralta‐Tapia et al., Laudon and Löfvenius, We preassigned model cells on south and north facing slopes in the Bruntland Figure  to serve18O uniformly in the catchment, both values feasible for a midwinter snowpack at the Krycklan climate [Laudon and Löfvenius, Efrac and Mfrac were given equilibrium fractionation values of 15‰ and 3.5‰ [Gat and Gonfiantini, Ellehoj et al., We initialized the model with a snowpack of 200 mm and an isotopic composition of −25‰ in δ Using 11 years of daily climate data, we calculated an average for each day of the year, and fitted a polynomial function through these averaged data to represent a “smooth evolution” of the climatic transition from winter to spring Figure . These s18O ‰), snowmelt flux exiting the snowpack (mm d−1), and isotopic composition of the snowmelt water (δ18O ‰).We ran the model with the averaged climate drivers and extracted model outputs for the north and south facing slopes for four variables: water stored in the snowpack (SWE) (mm), isotopic composition of the snowpack , with an average rate of 0.12 mm d−1. Around day 100, the interception storage is unloaded due to above zero air temperatures, according to equation (S34). After the unloading, the ground snow storage is lower than in the “no canopy” scenario, giving a higher combined sublimation rate of 0.47 mm d−1 from ground snow and interception storage than ground snow storage alone.Snow storage in the ground snow Figure a is progMoser and Stichler, Stichler et al., Gustafson et al., Koeniger et al., Moser and Stichler, Koeniger et al. [The isotopic melt‐out process from the snowpack is well documented in the literature, but there is less work on the sublimation enrichment of snowpacks. Nevertheless, the influence of sublimation on the isotopic composition of snow has been convincingly shown [r et al.  found anThe effect of snow sublimation on the ground snow isotopic composition Figure b shows aAir temperature exceeds 0°C on day 101 Figure c. The inMarks and Winstral, Rinehart et al., Earlier snow ablation in the canopy‐covered scenarios is somewhat counterintuitive, because canopy sheltering can postpone completion of snowmelt [−1 was not exceeded to start the melt‐out process  Bogus Creek located at snow/water transition zone in Idaho, USA and (2) Krycklan located in the Swedish boreal forest with a colder winter and a more persistent snow cover  withWout j (m) is the snowmelt runoff from the snowpack in a given cell; imelt j (‰), isotope ratio of the snowmelt water in a given cell; and Ncell is the number of model cells in the catchment.To compare the simulated isotopic composition of snowmelt to that of actual snowmelt samples, we extracted the spatially distributed simulated meltwater flux and its isotopic composition for each time step. From these data, we calculated the flow‐weighted catchment average of meltwater isotopic composition icomp to weight the simulated isotope ratio in snowmelt with the simulated flux of snowmelt water between lysimeter sampling days:Mk is the day number of snowmelt lysimeter measurements (in relation to simulation output time steps 1–150), and k goes from 1 to total number of lysimeter sampling days at each site.Because snowmelt lysimeters integrate the isotopic signal of snowmelt between the sampling days, for comparison purposes we calculated another flow‐weighted sum Mfrac ), TThigh ), and apow ). The first two influence the level of isotopic fractionation during snowmelt and sublimation, respectively, and the latter four affect the snow accumulation and melt processes supporting information (S1).The steps above resulted in pairs of observed and simulated values for both SWE and isotopic composition of snowmelt. We performed 10,000 Monte Carlo simulations varying six parameters in order to find parameter values which resulted in good agreement between observed‐simulated pairs. Varied parameters and their ranges were  to Yang  in equatGupta et al., Ala‐aho et al. [qthres in the CDF that maps exactly 100 simulations above it for SWE where the aim to is find high KGE values, and 1 – qthres for MAE, where we aim to find low error values. The 100 model runs for which the GOF was above qthres (for KGE) and below 1 – qthres for MAE were then retained as the behavioral model runs. We used “dotty plots” [see e.g., Beven and Freer, We used a single goodness‐of‐fit (GOF) metric for both observation‐simulation pairs to differentiate between rejected model runs and those accepted as “behavioral”. The Kling‐Gupta efficiency statistic (KGE) [o et al. . Each pa5.2Our model can match the overall level of depletion, the trend of progressively enriching meltwater and to some extent the variability of the snowmelt isotopic composition for four winters at the two field sites Figure . TypicalEfrac and Mfrac are visualized for both catchments as dotty plots  leads to lowest errors between values −2.5 and −7.5‰ in both catchments, demonstrating the relevance of incorporating snow sublimation fractionation at both sites. In Krycklan, the parameter affecting the intensity of melt‐out process (Mfrac) produces low errors throughout the sampled range, whereas in Bogus values close to zero result in low errors, suggesting that the melt‐out process was not apparent for the simulated winter in Bogus. Parameters influencing snow accumulation and melt are not shown, but of them apow and ccorr were identifiable in both catchments, whereas the threshold temperatures showed lesser sensitivity.The ranges for behavioral parameter values for the isotope fractionation parameters s Figure . The parOverall, our empirically based “proof‐of‐concept” test against field data shows how the model is capable of capturing the level and progression of the catchment averaged isotopic composition of snowmelt water in two different snow environments Figure . Field sEfrac. The optimal range for the parameter  the model mean error would increase. The optimum range for Efrac is more consistently greater than zero and more identifiable in Krycklan than in Bogus. This may be caused by more canopy cover in Krycklan allowing additional fractionation through sublimation from the interception storage  could be set higher, because the theoretical equilibrium fractionation factor decreases in cold air temperatures (approximately 20‰ in −30°C) [Ellehoj et al., Efrac. The kinetic isotope fractionation is enhanced in high temperature and low relative humidity, but environments with seasonal snowpacks typically exhibit low air temperature and high humidity over winter  based on model testing and theoretical considerations (see equation Taylor et al., The fractionation parameter for snowmelt g et al.  show howVarhola et al., Carey and Quinton, Blöschl et al., Laudon et al., Schmieder et al., Ala‐aho et al., Our spatially distributed process‐based formulation allows the snowmelt to occur at different rates and onset times in different parts of the catchment Figure , dependiBlöschl et al., Bowling et al., Winstral et al., Broxton et al., Essery et al., Bowling et al., Jordan, Tarboton and Luce, Pomeroy et al., Essery et al., Lehning et al., Liston and Elder, Pomeroy et al., Broxton et al., Walter et al., Our process‐based snow module to simulate SWE is what one could call “minimalistic” in terms of the processes included and the complexity with which they are conceptualized. One major missing model component is wind redistribution of snow that could make our approach unsuitable especially for complex mountainous terrain [Ala‐aho et al., Claassen and Downey [Taylor et al. [Feng et al. [As for any numerical environmental modeling, our approach is based on the need to calibrate the fractionation parameters against field observations. Here we use samples of snowmelt, but in a parallel study [d Downey , Taylor r et al. , and Feng et al. . However7We present a novel parsimonious modeling approach to simulate for the first time the spatially and temporally variable isotopic composition of snowmelt at the landscape scale. The resulting isotope ratios of snowmelt can be used in increasingly common tracer‐aided modeling studies to better understand the integrated nature of flow, mixing, and transport processes in snow‐influenced regions. The model‐based estimates for snowmelt isotopes can serve as input for tools such as end‐member mixing analysis, hydrograph separation, groundwater recharge source estimation, or tracer‐aided hydrological model applications.Poor estimates for the snowmelt isotope input signal have been identified as a major source of uncertainty for the above techniques in northern snow‐influenced environments. Our new model shows promise in producing an improved spatiotemporal estimate for snowmelt isotopes, which leaves the subsequent numerical technique, whatever it may be, with fewer degrees of freedom to constrain the water flow, mixing, and transport processes in the landscape. Furthermore, the model introduces a new methodology for simulating the sublimation enrichment of heavy isotopes in canopy‐intercepted snow. Isotope alterations caused by canopy interception can be important to account for in trace‐aided techniques where the hydrological partitioning of vegetation canopies is of interest.Our model is relatively simplistic, and in its current form may not transfer well to some snow environments; such as mountainous or tundra areas where wind redistribution is important, or rain‐snow transition zones where rain‐on‐snow events are common. On the other hand, a major advantage of the parsimonious isotope routines is that they can be effortlessly incorporated to any snow accumulation and melt model that explicitly accounts for snow sublimation. Therefore, the isotope routines can readily be applied, tested, and further developed using existing snow models and isotope data sets in contrasting environmental settings. Our work shows considerable promise in the model's plausible process representation in a theoretical simulation exercise, and an empirically based test in two field sites with contrasting snow conditions, but further model testing in different snow environments is needed.Supporting Information S1Click here for additional data file.


Coiled‐coils are found in proteins throughout all three kingdoms of life. Coiled‐coil domains of some proteins are almost invariant in sequence and length, betraying a structural and functional role for amino acids along the entire length of the coiled‐coil. Other coiled‐coils are divergent in sequence, but conserved in length, thereby functioning as molecular spacers. In this capacity, coiled‐coil proteins influence the architecture of organelles such as centrioles and the Golgi, as well as permit the tethering of transport vesicles. Specialized coiled‐coils, such as those found in motor proteins, are capable of propagating conformational changes along their length that regulate cargo binding and motor processivity. Coiled‐coil domains have also been identified in enzymes, where they function as molecular rulers, positioning catalytic activities at fixed distances. Finally, while coiled‐coils have been extensively discussed for their potential to nucleate and scaffold large macromolecular complexes, structural evidence to substantiate this claim is relatively scarce. We discuss examples of coiled‐coils as molecular spacers as well as coiled‐coils that communicate conformational changes along their length. We summarize recent examples of molecular rulers and the implications of confining catalytic activity to a fixed position. Finally, we discuss the role of coiled‐coils in scaffolding protein complexes.In 1952, Francis Crick described a new type of protein structure, which he called the coiled‐coil abcdefg, in which hydrophobic amino acids at positions a and d are conserved  is a useful resource for structural and cell biologists alike. The rest of this review will focus on the biological roles of coiled‐coil domains.Based on the underlying sequence repeats that govern their assembly, coiled‐coils can be reliably predicted from primary sequence While at least one coiled‐coil has been shown to possess catalytic activity Thermotoga maritima with a predicted coiled‐coil domain, was observed to span the periplasmic space Early studies in the 1990s identified a number of coiled‐coil proteins with apparent roles as molecular spacers. Omp‐α, an outer membrane protein in The longest coiled‐coil identified to date, found in the protein Giantin, is remarkably well conserved in length, but not sequence, in vertebrates Table . Since iSeveral other long‐coiled‐coil proteins are found on the Golgi, where they are typically anchored to the membrane via a transmembrane domain or by binding to a small GTPase  protein contains a 1500 amino acid coiled‐coil separating globular N‐ and C‐terminal domains which bridge the minus end‐directed microtubule motor protein complex dynein to the plasma membrane during metaphase Caenorhabditis elegans are Sas‐6 and Bld10p. Sas‐6 comprises an N‐terminal coiled‐coil domain and C‐terminal dimerization domain that cooperate to form a ninefold symmetric assembly of radiating spokes Chlamydomonas give rise to shorter spoke lengths and increased frequencies of centrioles with lower symmetry Tetrahymena missing Bld10 show microtubule misorientation and basal body disassembly Centrioles are intracellular organelles found in most eukaryotic cells and an important component of centrosomes in the metazoan lineage, where they act as the microtubule organizing center (MTOC) of the cell. Centrosomes are essential for organizing the mitotic spindle during cytokinesis. In organisms with flagella and cilia, the mother centriole becomes the basal body of the cilium or flagellum. Centrioles are, therefore, critical regulators of ciliogenesis and the associated capacities for locomotion, sensation, and signaling in these organisms. Centrosomes are abundant in coiled‐coil proteins, the evolution of which led to the formation of a signaling hub that scaffolds ancestral eukaryotic proteins crucial for multicellular development Methanococcus jannaschii provides a molecular explanation for how two sequences a fixed distance apart are recognized The type I restriction‐modification enzymes are another elegant example of the use of a coiled‐coil molecular spacer to guide catalytic activity. Type I restriction‐modification enzymes recognize two specific dsDNA sequences separated by a spacer of definite length, but cleave randomly away from the recognition sequences. They comprise specificity, methylation, and restriction subunits. The crystal structure of the specificity subunit of A similar structural organization of DNA‐binding domains can be observed in the MerR family of bacterial transcriptional activators While the Golgins and other coiled‐coils exhibit high levels of sequence substitution, the coiled‐coils of the cohesin subunits are the most conserved naturally occurring coiled‐coils Table , Fig. 3.Rad50 is a central regulator in the DNA damage response pathway. Like the SMCs, Rad50 comprises a long internal coiled‐coil that folds back upon itself to bring globular N‐ and C‐terminal domains together to form a functional ABC ATPase domain Fig. . The hinThe coiled‐coil tail domain of myosin, highly conserved in both length and sequence Table , self asAllosteric communication along coiled‐coils requires concerted changes in the register and packing of the chains. The capacity to transmit structural changes along the length of a coiled‐coil has recently been shown to be essential for the activity of motor protein complexes involved in the cellular transport of cargo.Cytoplasmic dynein is a minus end‐directed motor protein complex that drives long‐range retrograde transport of cargo along microtubules. Dynein thereby plays a key role in cellular processes such as fast axonal transport, Golgi vesiculation, and mitosis. Crystallographic and cryo‐electron microscopy studies have provided important insights into the chemo‐mechanical cycle of dynein  is a major component of the outer membrane of Gram‐negative bacteria, where it plays important roles in pathogenicity and viability. LPS comprises a conserved membrane anchor, lipid A, and a short conserved core oligosaccharide that links lipid A to an immunogenic polysaccharide, called the O‐antigen, of variable chain length. The O‐antigen has been shown to be vital for evading detection by the host immune system bdD Fig. . WbdA isbdD Fig. . InsertiA second example of a molecular ruler was recently found in the Rho‐associated coiled‐coil kinase (ROCK2), a serine/threonine protein kinase. The Rho kinases are critical regulators of the actin cytoskeleton, phosphorylating the regulatory myosin light chain (RMLC) to induce actomyosin contraction. Chemical inhibition of ROCK, or expression of a dominant negative kinase‐dead ROCK, results in the complete loss of actin stress fibers in cells The implications of this model are profound. Only one kinase is widely believed to be constitutively active in the cell: casein kinase 2 (CK2) Long coiled‐coil proteins encode an enormous repertoire of surface epitopes, in addition to potentially linking functional domains or communicating conformational changes. This raises the obvious question of whether in fact the surfaces of coiled‐coil proteins are widely used as molecular scaffolds. Surprisingly, examples of their use to scaffold multi‐subunit protein complexes or to recruit enzymatic activities GLUED, a component of dynactin, are long coiled‐coil domain‐containing proteins. The structure of the dynactin‐BICD2 complex The motor protein dynein depends on a large protein complex called dynactin for its function. Binding of dynactin and a cargo adapter converts dynein into a processive, unidirectional motor along microtubules Proteomic studies frequently pull out coiled‐coil proteins in screens for interaction partners, but most of the interactions remain to be validated biochemically and structurally. In this respect, it is worth noting that the interaction of RhoA with the coiled‐coil of ROCK has recently been challenged The coiled‐coil is a remarkably versatile motif due to its inherent capacity to give rise to a polymer of, hypothetically, unlimited length and precisely adjustable mechanical properties. Coiled‐coil domains vary in length from the short to the extremely long, and from being almost invariant in sequence to hypervariable. Some coiled‐coils appear to function simply as molecular spacers while others have evolved the capacity to communicate conformational changes along their length. These properties make the coiled‐coil an essential component of the proteome, one that underlies the structure of organelles, facilitates critical maintenance, repair, and replication of genetic material, drives transport and trafficking of material within the cell, and correctly positions enzymatic activities.While coiled‐coils represent a significant proportion of the eukaryotic proteome, there are relatively few high‐resolution structures of full‐length coiled‐coil‐containing proteins. Furthermore, crystal structures of coiled‐coils illustrate the plasticity of the motif, with many coils exhibiting non‐canonical packing interactions. Whether these structures, which are often fragments of the natural coiled‐coil, represent conformations along the normal trajectory is open to debate given the contributions of lattice packing interactions While the canonical coiled‐coil was postulated over 60 years ago, new twists on the possible structures that can be formed by coiled‐coils are still being discovered. Future challenges lie in understanding the mechanical properties of individual coiled‐coils and how they are suited for their biological functions. In this regard, the de novo design of novel coiled‐coil structures has the potential to enhance our understanding of the structure and properties of existing, naturally occurring coiled‐coils.


Interfacing proteins with electrode surfaces is important for the field of bioelectronics. Here, a general concept based on phage display is presented to evolve small peptide binders for immobilizing and orienting large protein complexes on semiconducting substrates. Employing this method, photosystem I is incorporated into solid‐state biophotovoltaic cells. Due to the high internal efficiency of the multiprotein complex photosystem I (PSI) to perform light harvesting and charge separation, this key component of photosynthesis potentially enables biophotovoltaic devices in which the active components are biologically grown rather than chemically synthesized. However, owing to the size and structural complexity it remains a challenge to assemble well‐oriented monolayers of PSI on surfaces, which is critical for device functionality due to the directional bias of the electron‐transfer process. We applied phage‐display techniques to identify short binding peptides that afford near‐perfect control over the orientation of PSI in self‐assembled monolayers (SAMs) once these peptides are functionalized with a surface anchoring group. Almost 100% orientation of PSI on a semiconductor substrate was achieved. We characterized the orientation in junctions by using soft, conformal top contacts comprising eutectic gallium‐indium (EGaIn), and using single‐complex conducting atomic force microscopy (c‐AFM), and demonstrated functionality by fabricating solid‐state bulk heterojunction (BJH) solar cells.Phage display (PD) is a very powerful method for the selection of peptides that bind a wide variety of molecules and substrates.Thermosynechococcus elongatus, which has found widespread use as a model system for structural and function studies. PSI from T. elongatus consists of main subunits shown in Figure4S4) clusters, one calcium ion, 22 β‐carotene, 96 chlorophyll a, 1,2‐dipalmitoyl‐phosphatidyl‐glycerol, one 1,2‐distearol‐monogalactosyl‐diglyceride, and two phylloquinone molecules. Under certain conditions, PSI complexes trimerize with a threefold rotation symmetry axis (C3) oriented perpendicular to the membrane . The PsaL subunit connects the PSI monomers within the trimer configuration. PsaA and PsaB are the largest subunits containing eleven transmembrane helices. Both subunits bind a large number of chlorophyll molecules and coordinate the electron transport chain (ETC), which is lining the inside of the protein complex. The subunits PsaC, PsaD, and PsaE form a crescent shape and are located at the stroma site of the thylakoid membrane. PsaC coordinates the two terminal Fe4S4 clusters FA and FB of the ETC.A natural key building block for transforming light into chemical energy is the multiprotein complex PSI from thermophilic cyanobacteria such as 0 (Chla), A1 (phylloquinone), FX, FA, and FB (Fe4S4 clusters) within the complex to the external ferredoxin charge carrier. The corresponding positive charge generated at the center of P700+• remains at the opposite side of the protein complex (the lumen side of the thylakoid membrane) and is recharged by electrons from cytochrome c6 (and plastocyanin). The process of light harvesting and charge separation is very efficient, with an internal quantum efficiency close to unity. For that reason, PSI complexes have been incorporated into bio‐photonic devices, biosolar and biofuel cells.Photons harvested by chlorophyll molecules are transferred to the reaction center P700, where charge separation takes place. At P700, the special pair of chlorophylls forms an excited state with a 1.3 V potential difference. From there, the electron is transferred via the primary electron acceptors AB cluster points directing into the substrate; one peptide produces SAMs with nearly 100% orientation. We determined the orientation by c‐AFM on single complexes and using EGaIn on the macroscale; the orientation of PSI with respect to the surface of a bottom electrode gives rise to direction‐dependent asymmetry in tunneling currents. We demonstrated the functionality of oriented SAMs of PSI by assembling them on indium tin oxide (ITO) electrodes in BJHs biophotovoltaic solar cells where the magnitude of the open‐circuit voltage (Voc) correlated to the degree of orientation.In this Communication, we demonstrate a new phage display protocol to select small peptide binders against PSI trimers chemically bound to the surface of a solid substrate. From this selection procedure, we identified three linear 12 mer peptides with high affinity against the stromal side of PSI. After chemical synthesis and the introduction of a surface anchor, these peptides can bias the orientation of PSI in SAMs such that the electron accepting FT. elongatus was purified as a trimer and attached to an epoxide‐modified surface (see Supporting Information), which resulted in functionalization of amino groups to cause PSI to orient randomly. Next, a commercial library of filamentous bacteriophage M13 expressing 12‐amino acid long random‐peptide sequences in fusion with their p3 protein (NEB #E8110S) was panned against the immobilized PSI trimer targets. Although the protocol of the vendor was followed, after three rounds of panning and amplification, no selection was achieved. Instead, wild‐type phages were recovered after the final amplification step.Photosystem I from FigureAiming for a reduction of the number of cycles that could favor the selection of wild‐type phages, we developed a new phage display method that leverages enzymes conjugated to the viral particles Figure2A,B. UEscherichia coli to amplify single‐phage clones. The single clones were sequenced  and their binding affinity toward PSI was tested. We prepared three different surfaces: the first contained PSI without any preferential orientation as utilized for the panning procedure; the second was coated with a monolayer of bovine serum albumin (BSA); and the third was decorated with PSI trimers oriented with the help of an anti‐PsaC antibody  with the lumen side facing away from the surface and therefore exclusively accessible for binding  in a modified phage‐(enzyme‐linked immunosorbent assay) (phage‐ELISA) by incubating the surfaces in a solution of single clones of M13 conjugated to HRP. After washing, we added the fluorogenic substrate and determined the relative amount of bound phages via the fluorescence intensity of the surface in real time. By comparing the signal from the randomly oriented PSI to those bound to PsaC antibodies, we could differentiate between peptide sequences that bind PSI indiscriminately versus those that selectively bind the desired stromal side. The outcome of this binding assay is shown in Figure Afterward, the eluted phages were used to infect After identifying peptide sequences that bind PSI, we characterized the ability of these peptides to orient PSI on a conducting substrate by c‐AFM. Therefore, the peptide sequences were modified at the C‐terminus with a phosphorylated serine residue allowing binding to an ITO surface.FigureI–V curves depending on their orientation. The origin of this rectification on Au substrates was recently elucidated and is most likely due to the permanent dipole of the PSI protein scaffold and not the cofactors of the ETC.B side or PsaC toward the substrate , a higher electrical current is measured at negative bias compared to the electrical current at positive bias giving rise to I–V data that are asymmetric about zero. This is the same orientation afforded by the PD‐selected peptides. The same orientation was confirmed on ITO using DHAP as short linker molecule by comparing with data from biophotovoltaic devices incorporating PSI.I–V data are symmetric). Guided by these observations, we analyzed the three different substrates with the three different peptides and an additional substrate bearing a scrambled sequence of peptide ALF (ALFHYNTHGSLH) acting as directors for the assembly of PSI and the short directing molecule DHAP. For convenience purposes, only the first three amino acids of each sequence will be used as identification.To gain insights into the orientation of PSI, we performed c‐AFM studies on the three different peptide‐immobilized PSI layers and the DHAP directing linker as depicted in I–V ramping to record the electrical characteristics of individual PSI trimers, examining at least 100 trimers for each of the three peptide linkers. The resulting I–V curves show orientation‐dependent electrical behavior as described above. The expected, downward configuration of PSI shown in Figure TableI–V plots for IQA (P2) can be found in Figure S3, Supporting Information).We used Pt/Ir probes for c‐AFM studies in contact mode on a sample at zero voltage to record the topography of the PSI layers . From these data we identified individual PSI trimers on the ITO surface as an approximately round, bright spot. We then set the c‐AFM to J/V characteristics of the peptides (without PSI) and SAMs of PSI with the peptides with PSI complexes by computing the differences of ∆log|χ|. This value reflects the combined influence of the population of PSI trimer orientations—it gives insight into how the distribution of orientations and the assemblies of the underlying peptides influence devices as opposed to looking at isolated trimers. By comparing ∆log|χ| between the bare peptides and the SAMs of PSI on the peptides we can ascribe any observed asymmetry to either or both.After quantifying the orientation of PSI complexes one by one via c‐AFM, we investigated the macroscopic electrical properties of SAMs of PSI using the same four peptides and the short linker DHAP using EGaIn as a top electrode. In a recent study, SAMs of partially oriented PSI using two different short linkers showed orientation‐dependent electrical properties using EGaIn as a top electrode.J at −1 V)/(J at +1 V) according to the wiring of c‐AFM (which is backward from EGaIn).We fabricated test‐bed devices by incubating PSI with the modified peptides and subsequently drop‐casting the PSI‐peptide complexes onto clean ITO substrates. In comparison to macroscopic studies, the ITO surface was functionalized with an SAM of DHAP as described elsewhere.FigureThe trend observable in our results is the increasing absolute value of ∆log|χ|. It is 0.097 for RDQ, 0.099 for LAT, 0.551 for ALF, and 0.737 for IQA  while positive charges (holes) remain at the P700 donor site. As a consequence of charge separation, a dipole between the semiconductor electrode and the organic BHJ is created, which effectively modifies the work function of the electrode.VOC is sensitive to the work function difference between the bottom and the top electrode, the dipole orientation can be determined from the shift in work function. We chose the same material, ITO, as an electrode to allow direct comparison with the c‐AFM and EGaIn results. We immobilized the PSI monolayer as described above. Additionally, we immobilized PSI with DHAP, which directs the majority of PSI trimers with the FB site downward to the surface (same orientation as peptides) as a control. We formed the active layer by spin coating a 1:4 mixtures (by wt%) of the p‐type conjugated polymer poly (MEH‐PPV) and the fullerene derivative phenyl‐C61‐butyric acid methyl ester (PCBM) in chlorobenzene on the SAMs of PSI. As the last step of device fabrication, we deposited either electron‐extracting (LiF/Al) or hole‐extracting (MoO3/Al) electrodes atop the MEH‐PPV:PCBM/PSI/peptide/ITO stack by thermal evaporation to produce normal and inverted photovoltaic devices, respectively , VOC increases. This behavior implies that the PSI monolayer shifts the vacuum level, lowering the work function of ITO, confirming that a sufficiently large fraction of the dipoles in the PSI layer are directed with FB toward ITO . These results clearly indicate that all peptides direct a larger fraction of PSI downward with FB site being arranged in close proximity to the semiconductor and not to the organic material compared to the directing layer consisting of the small molecule. Similar results were obtained for the inverted solar cell configuration containing MoO3/Al top electrode , e Figure B. There The orientation of photoactive proteins such as PSI on a surface is of major importance either to study their biophysical behavior or to exploit their superb light‐induced charge separation capabilities in bioinspired solar and fuel cells. We used phage display to identify binders against the photosynthetic complex PSI. The selection strategy was designed in such a way that only one round of selection was necessary to obtain binders and that these binders are directed to a desired side within this megadalton multiprotein complex, i.e., the stromal side (where electrons are ejected after photoexcitation). Three 12 mer sequences, obtained by phage display, enabled the immobilization of PSI with the majority of complexes oriented with the opposite face toward a semiconductor surface after the peptides are modified with an appropriate surface anchoring group. One of the peptides was able to direct almost all PSI molecules exclusively in one orientation. It is crucial that the orientation and its effects be characterized rigorously in the dark, over large areas and in the light and that the orientation survive processing into thin‐film devices. Therefore, we characterized single PSI complex and SAMs and incorporated PSI‐modified ITO into photovoltaic devices.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


Originating from primary tumors and penetrating into blood circulation, circulating tumor cells (CTCs) play a vital role in understanding the biology of metastasis and have great potential for early cancer diagnosis, prognosis and personalized therapy. By exploiting the specific biophysical and biochemical properties of CTCs, various material interfaces have been developed for the capture and detection of CTCs from blood. However, due to the extremely low number of CTCs in peripheral blood, there exists a need to improve the efficiency and specificity of the CTC capture and detection. In this regard, a critical review of the numerous reports of advanced platforms for highly efficient and selective capture of CTCs, which have been spurred by recent advances in nanotechnology and microfabrication, is essential. This review gives an overview of unique biophysical and biochemical properties of CTCs, followed by a summary of the key material interfaces recently developed for improved CTC capture and detection, with focus on the use of microfluidics, nanostructured substrates, and miniaturized nuclear magnetic resonance‐based systems. Challenges and future perspectives in the design of material interfaces for capture and detection of CTCs in clinical applications are also discussed. In t2By presenting the possibility of being exploited to discriminate CTCs from normal blood cells, the biophysical and biomechanical properties of CTCs have gained much attention.CTCs were first identified by Ashworth in 1869 when he microscopically inspected the blood from metastatic cancer patients. Due to their similarity to the metastatic cancer cells, CTCs identification were initially done by trained cytologists in term of elongated nuclei and fragmentation of the chromatin based on Papanicolaou's criteria for malignancy.2+‐independent cell‐cell adhesion in epithelia.In addition to the aforementioned biophysical properties, CTCs also express some unique biochemical markers that can be utilized for selective CTC capture and isolation. Among these biochemical markers, EpCAM and human epidermal growth factor receptor 2 (HER2) are two typical biochemical markers frequently used for the isolation and enrichment of CTCs. EpCAM is a transmembrane glycoprotein mediating Ca3TableBased on the differences in biophysical properties between CTCs and normal blood cells described above, label‐free strategy for direct capture and isolation of CTCs can be developed. As a powerful separation approach, microfluidic technique with small sample‐volume requirement, fast processing times, multiplexing capabilities and large surface area‐to‐volume ratios, offer a good option for label‐free CTCs capture and isolation.FigureAs a relatively straightforward technique with low cost, size‐based microfluidic filtration is one of the first approaches employed for CTCs capture and isolation, based on the fact that CTCs are larger than blood cells such as white blood cells (WBCs) and red blood cells (RBCs).2 cells mL−1). Kamande et al. reported a modular microfluidic system containing three different functional regions by which isolation, enumeration, and phenotyping of CTCs could be finished in one device.Additionally, microfluidic devices with functionalized microchannels have been developed for CTCs capture and isolation.By combing the immunomagnetic separation strategy and microfluidic technique, Immunomagnetic‐based microfluidic systems have also been developed for efficient CTCs capture and isolation.High deformability is a distinctive biomechanical property for cells circulating in the peripheral blood, especially for CTCs with larger size than normal blood cells in order to rapidly go through capillaries with small diameters of 6–8 μm and successfully metastasize.In a straight microfluidic channel, fluid shear can generate lateral forces to cause transverse migration of particles.4TableIn tissue engineering and regenerative medicine, nanostructured substrates have been widely employed to mimic the natural extracellular matrix (ECM) and basement membrane.FigureInspired by the surface components of cells, the nanowire and nanopillars‐based substrates have been designed and utilized to make use of the surface adhesion of the cells and aid the capture of CTCs in blood samples. For example, Wang et al. firstly utilized anti‐EpCAM‐coated Si nanopillars (SiNPs) substrates to identify and capture CTCs Figure3A. Usi−1).Nanodot and nanosheet substrates have also been demonstrated to show efficient CTCs capture ability. The dot size and density were controlled by the voltage applied and could be easily reproduced and tuned. Five tumor cell lines of interest were examined and they were either overexpressed with EpCAM antigens or without EpCAM antigens on their cell membranes. Although the aspect ratios of nanodots were small, the efficiency of specific cell capture by anti‐EpCAM conjugated to the nanodots, was enhanced by four to five times in comparison with smooth films Figure C.95 The 2, and poly(lactic‐co‐glycolic acid) (PLGA) can be electrospun to form desired nanofibers with controllable diameters and lengths. Zhang et al. fabricated TiO2 nanofibers of 100–300 nm diameter from a spun composite of titanium n‐butoxide and polyvinyl pyrrolidone  and ‐COOH groups in acid‐oxidized MWCNTs. Due to the high affinity interacions between the boronic acid groups of APBA and the carbohydrate on cell surface, the K562 cells could be efficiently captured by the APBA‐functionalized MWCNTs films. Compared to bare APBA films, the functionalized MWCNTs one not only exhibited more boronic acid groups for K562 cell recognition, but also provided enhanced local cell‐MWCNTs interactions, which improve K562 cells' adhesion on its surface. Furthermore, the high electrical conductivity of MWCNTs maked the APBA‐MWCNTs film a good electrode for subsequent cell electrochemical sensing, presenting a promising way for efficient capture and highly sensitive electrochemical detection of CTCs. In another report, King et al. explored a method to more efficiently capture leukemic and epithelial cancer cells from flow by altering the nanoscale topography of the inner surface of P‐selectin‐coated microtubes.Nanotubes and nanopores have also been reported to have great potential for CTCs capture and isolation. For example, functionalized multiwalled carbon nanotubes (MWCNTs) films have been successfully used for K562 cells (leukemia cells) capture and electrochemical sensing Figure E.99 They5μNMR) exploits magnetic resonance technology to detect target labelled with immunospecific magnetic nanoparticles (MNPs), showing great potential in rapid and highly sensitive biodetection.μNMR are superparamagnetic and have small size (tens of nm), which is different from the conventional magnetic nanoparticles used in immunoseparation. The mechanism of μNMR‐based sensing technique is based on the phenomenon that MNP‐labeled targets exhibit faster relaxation of NMR signals due to local magnetic fields created by MNPs.μNMR‐based platform have been developed for rapid and sensitive detection of biomolecules including nucleic acids, proteins, bacteria, and tumor cells.μNMR‐based technique do not need sample purification procedures and can simultaneously achieve target capture and detection, gaining much attention in the fields of CTCs capture and detection. This section will briefly introduce recent developments of μNMR‐based biosening systems and their potential applications in CTCs capture and detection.As a novel sensing technology, micro‐nuclear magnetic resonance  was developed by Lee et al.μNMR‐based CTC capture and detection.Based on the “le Figure4A.102 FigureTill now, different models of μNMR devices with miniaturized system for CTCs capture and point‐of‐care detection have been developed. The miniaturization of μNMR system endows the following advantages: 1) improving detection sensitivity by reducing sample volumes and increasing the concentrations of targets; and 2) generating stronger radio‐frequency NMR magnetic fields due to the use of smaller magnets in miniaturized system. Figure 6Once CTCs are captured and enriched, subsequent detection and identification are needed to investigate their origin and genetic profile from which more valuable insight into the biology of metastasis can be obtained.Most CTCs immunological identification assays use different fluorescent dyes to simultaneously stain cytokeratins  and leukocyte antigen CD45 (exclusion marker). The cell staining process is always carried out in situ in microfluidic‐ and nanostructured substrates‐based platforms. For example, in size filtration‐based microfluidic system with microcavity arrays, two fluorescent immunological probes of FITC‐labelled anti‐CD45 antibody and PE‐labelled anti‐EpCAM antibody were employed to detect and identify CTCs captured on the microcavity arrays.N‐isopropylacrylamide) (PNIPAAm) brushes‐modified SiNWs substrate (Figure For approaches of CTCs detection and identification, there are still two factors needed to be taken into consideration. Firstly, heterogeneity among CTCs is a problem that can not be ignored for CTCs detection and identification, which makes cell‐to‐cell variations occur in same cancers and only a very small fraction of CTCs that may eventually acquire the ability to seed the metastatic tumor. Hence, how to characterize molecular, phenotypic and functional difference of CTCs at the single‐cell level is a critical problem that need to be reviewed. Lee et al. reported a laser scanning cytometry‐based method for CTCs detection and identification, by which automated and rapid characterization of physical and functional cellular properties such as size, shape and signaling proteins of CTC at the single‐cell level was quantitatively achieved.e Figure B. This pe Figure C. By pre7In the previous sections, we described various advanced materials interface mainly based on microfluidics, nanostructured substrates, and micro‐nuclear magnetic resonance systems for CTCs capture and detection. Although promising results have been achieved by these interfaces in terms of capture efficiency and detection sensitivity, most of them still remain in the laboratory level and little of them unequivocally shows clinical validity and utility.3–106 cells, thereby only giving the average genotypic or phenotypic characteristics of the cell population. In addition, the way the isolated cells are cultured to expand CTC numbers is not recommended, given that cancer cells have a feature that modifies their characteristics to survive when the surrounding microenvironment is changed.Beyond the issue of capturing and isolating CTCs, achieving a better understanding of the molecular characteristics of CTCs is also important from which new biomarkers for efficient CTCs capture and isolation can be discovered. However, traditional CTCs molecular analysis is always performed by using large ensembles on the order of 10


We present a 57‐year‐old man with a 1.5‐cm‐diameter blood cyst in the left ventricle, which was incidentally detected by conventional diagnostic echocardiography before colon surgery. The cyst originated from the papillary muscle, and the pathological findings were compatible with a cardiac blood cyst. Most cardiac tumors are benign and incidentally detected. Blood cysts are rare benign lesions. Small blood cysts in the cardiac chamber are sometimes recognized during operations in infants, and they generally show no clinical adverse effects because of their small size. Cardiac blood cysts are very rarely detected preoperatively.A 57‐year‐old man was transferred to our hospital for treatment of an asymptomatic cardiac tumor. The tumor was incidentally detected during a preoperative work‐up for colon cancer. On examination, he was afebrile with no cardiac symptoms. A Levine II/IV pansystolic murmur was audible at the apex area without an arrhythmia. The patient's blood cell counts were normal, and his C‐reactive protein concentration was <0.1 mg/mL with normal renal and liver function. Chest radiographs showed no cardiomegaly and clear lung fields. Echocardiography revealed a 1.5‐cm‐diameter cystic mass in the left ventricle with moderate mitral valve regurgitation, and transesophageal echocardiography indicated that the tumor seemed to be attached the mitral chorda of the anterior leaflet (Fig. We could not rule out the malignant potential of the tumor and its possible risks of embolic stroke. We chose a superior septal approach to obtain an excellent operative view within the left ventricle. The tumor was attached to the rough zone of the anterior leaflet and was free from the chordaetendineae. A traction suture was placed in the tumor, and bloody fluid ran from the tumor, which finally collapsed Fig. . The tumThe pathological findings were compatible with a cardiac blood cyst Fig. . The tumCardiac blood cysts might spontaneously regress or rarely grow to sizes detectable by conventional prognostic procedures. Cardiac cysts may develop in any heart cavity.Okubo et al. In general, microscopic findings of a blood cyst are consisted of fibrous tissue covered with normal endothelium. No tumorous proliferative cells are found. The findings of our case are consistent with previously reported cases The optimal management of asymptomatic cysts has not yet reached consensus. Some clinicians routinely remove such cysts to exclude malignancy and avoid the potential risk of embolism, and others refrain from surgical resection of cystic masses that do not interfere with normal cardiac function.We have herein presented a case involving a 57‐year‐old man with an incidentally detected blood cyst in the left ventricle. The tumor originated from the papillary muscle and was attached to the rough zone of the anterior leaflet; it was successfully resected with a small amount of rough zone followed by repair of mitral valve regurgitation.None declared.HA and AM: participated in the design this study and helped competing an initial manuscript. YM: carried out its final manuscript. All authors read and approved the manuscript.


Virus‐surface‐mimicking decoration of deoxyribonucleic acid (DNA)‐entrapped polymeric nanoparticle with AuNPs is demonstrated to lead to enhanced cellular uptake, improved gene transfection, and particularly efficient near‐infrared photothermal therapy that cannot be achieved by both of them separately. This hybrid nanosystem represents a novel paradigm of multipurpose organic–inorganic nanoplatform, especially for cancer treatments. FigureGene therapy has shown great potency for treating various diseases, such as cancers.Drawing lessons from the viral topography, the present work reported a virus‐surface‐mimicking nanotechnology by decorating gene‐entrapped polymeric nanoparticles with clustered gold nanoparticles (AuNPs) Figure . This biMw = 1800 Da) was prepared at the optimal transfection N:P ratio of 20:1 and was used as the organic nanomatrix for the sequent fabrication of hybrid NPs. The nanocomplex possessed the surface zeta potential of +27 mV and the mean hydrodynamic diameter of 110 nm, as determined by dynamic light scattering . Citrate‐coated AuNP  was slowly added into the nanocomplex solution under vibration. Driven by electrostatic interaction, the nanocomplex would readily be covered by a high density of smaller AuNPs , reconfirming the successful manufacture of hybrid PEI1800/pGL‐3/AuNP nanoparticles. Upon AuNP addition, the enhanced hydrodynamic diameter of PEI1800/DNA naocomplex might associate with the charge neutralization occurring between the nanocomplex and the opposite charged AuNPs. As a consequence, the nanocomplex may be less compact than that without AuNP decoration.In a proof‐of‐principle experiment, a positively charged nanocomplex of plasmid pGL‐3 condensed with lowly toxic polyethylenimine  cells, monkey kidney fibroblast (COS7) cells, human hepatoma HepG2) cells, and mouse fibroblast (3T3) cells were tested to evaluate the universal adaptability of this strategy. Confocal laser scanning microcopy (CLSM) provided an intuitive inspection over the cellular uptake of YOYO‐1‐labeled plasmid pGL‐3. As shown in  cells, aThe electrostatic attractiveness of cell membrane to polycation/DNA nanocomplex plays a predominant role for its cellular entry. In principle, higher charge of positive nanocomplex benefits the intracellular delivery though it usually gives rise to the damages to cells.FigureBeing aware that the surficial AuNP clustering can facilitate the cell uptake of PEI800/pGL‐3 nanocomplex, it is interesting to make clear the resulting influence on the transfection performance. The in vitro transfection was therefore studied by luciferase assay in the 10% serum‐containing medium. As expected, AuNP attachment made a positive impact on the transfection so that the protein expression level was dramatically enhanced in all of the four transfected cell lines at the mass ratio of AuNP versus nanocomplex of 7:1 . As far as the promotion effect of pGL‐3 protein expression was concerned, the best outcome was detected in COS7 cells with approximately a 100‐fold enhancement. This correlated well with the finding that the AuNP‐induced enhancement of cell uptake was more distinguished in COS7 cells, validating the feasibility of improving the transfection by virtue of promoting the intracellular plasmid transport. Enhanced green fluorescent protein plasmid (pEGFP‐C1) was also used as the reporter gene for the transfection tests and the transfected cells were observed by CLSM. Compared with the controls using PEI1800/pEGFP‐C1 nanocomplex, inside the cells transfected with PEI1800/pEGFP‐C1/AuNP appeared significantly stronger green fluorescence regardless of the cell types Figure3A, whiThe relationship between the transfection efficacy and the introduced AuNP dosage has been explored . It was shown that as elevating the weight ratio (AuNP vs nanocomplex), the transfection efficacy took on a gradual increment followed by a plateau starting from the ratio at around 6:1. This finding was consistent with the obtained DLS data in terms of the zeta potential. It was found that the variation profile of the zeta potential also involved two stages, where the zeta potential intended to be insignificantly changed after the ratio reached the same ratio . Theoretically, the topography of PEI800/pGL‐3/AuNP nanoparticles would be slightly affected when the surficial AuNP attachment is close to saturation. Thereafter, further increasing AuNP amount would make few influences on the surface potential and the transfection efficiency. Based on the obtained results, therefore, a relatively higher ratio of 7:1 was exploited throughout this study to ensure the complete coverage of the complex surface with AuNPs. On the other hand, DLS data showed that the diameter of the hybrid NPs kept slowly growing along with the ratio increase. The continuous increase of the particle diameter from 210 to 270 nm after the ratio reached 6:1 may possibly associate with the minor aggregation at a higher AuNP dosage . However, such a slight change in the diameter appeared to insignificantly affect the transfection efficacy .A tetrazolium dye (MTT) based assay was carried out to study the influence of AuNP attachment on the cell toxicity of PEI1800/pGL‐3 nanocomplex. As shown in Figure S4 (Supporting Information), the cell proliferation was nearly not affected by AuNP attachment. The relative cell viability of AuNP‐free and ‐present nanocomplexes always remained above 90% in all of the four cell lines, suggesting the low cytotoxicity originating from the good biocompatibility of PEI1800 and AuNPs.WAuNP:Wcomplex = 7:1) appeared lots of dark spots representing the clustered AuNPs that cannot be detectable at all for the treatment using free AuNP. In addition, the comparison between TEM images revealed that a portion of AuNPs in the PEI1800/pGL‐3/AuNP system still remained in the free state. To a certain extent, this finding implied that the weight ratio of 7:1 used in this study can guarantee the saturated coverage of the nanocomplex with AuNPs.Rapidly proliferating tumor cells are more sensitive to heat shock than slowly proliferating cells through the mechanisms such as mitotic delay, cell cycle arrest, and plasma membrane damage.In summary, a virus‐surface‐mimicking nanotechnology was herein proposed to develop nonviral gene delivery nanosystem by electrostatically coating DNA‐entrapped polymeric nanoparticles with AuNPs. The resulting rough periphery composed of AuNP nanoclusters led to the significantly enhanced cellular uptake of DNA payload and consequently up to 100‐fold promotion of transfection efficacy as compared with the AuNP‐absent counterpart. Attractively, this hybridization approach allows the facile import of hyperthermia‐induction capability into the traditional gene delivery nanosystem, as demonstrated herein by the outstanding potency for the NIR photothermal therapy in cancerous HeLa cells. It is noted that this distinguished advantage highly relied on the success to form gold “nanoclusters” on the hybrid nanosystem, whereas both the parent nanocomplex and the AuNP separately failed under the identical NIR treatments. Further interests toward this nanotechnology would arise from its expandability to other inorganic NPs for the establishment of multipurpose gene‐based nanoplatforms, e.g., by using iron oxide NPs to combine gene therapy with the magnetic‐induced targeting and thermal therapy.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


The VistaCam® system  has been suggested as an adjunct to clinical examination for dental caries. This study assessed whether the digital scores obtained for tooth surfaces were affected by the colour of the carious lesions present and by the presence of saliva or blood on the tooth surface. The VistaCam intra‐oral ries, or with sound enamel and root surfaces, with or without overlying dental plaque biofilm. Teeth that had undergone root treatment or were stained by tetracycline were also assessed. Readings were taken in the dry state and after application of human stimulated saliva or venous blood onto the surface of the samples. VistaCam fluorescence scores for all samples were similar in the dry state, and when covered with saliva (P > 0.05), however a coating of dilute blood elevated the readings for most samples to a high level (P < 0.01), other than tetracycline stained teeth and dental caries (P > 0.05). Readings for healthy enamel were 0.9–1.1, and these increased up to 2.8 in the presence of blood. VistaCam fluorescence scores are not affected by dryness or moisture from the presence of saliva but increase when traces of blood are present. This problem needs to be taken into account when the device is used clinically, because blood from the gingival crevice is a common contaminant of tooth surfaces when patients have widespread gingival inflammation. There are also issues with elevated scores from background fluorescence from tetracyclines, which need to be considered when the system is in clinical use. Dental caries is one of the most prevalent dental conditions , and much emphasis has been placed on the detection of the disease at early stages. Radiographs have been used as an adjunct to clinical examination but suffer from concerns regarding ionizing radiation (White & Pharaoh 2014). There is current interest in optical devices which emit non‐ionizing radiation and are therefore inherently safe, allowing them to be used at frequent intervals to detect and monitor caries. Amongst these innovative technologies are fluorescence detection systems combined with intra‐oral cameras including the VistaCam®  camera (405 nm wavelength light) and the SoproLife®  (450 nm blue light and visible white light) .The 405 nm wavelength violet light emitted by the VistaCam elicits fluorescence from both inorganic and organic components of teeth . When imaging in fluorescence mode, structures containing porphyrin molecules, such as caries, stains  and mature dental plaque  emit visible red light when illuminated by violet light . The violet excitation light is not seen by the camera as it is removed by a filter located in front of the sensor. Image processing  allows the extent of fluorescence to be mapped using a look‐up table to a pseudocolour image. The colours align with numerical values for the pixels . These data may potentially be used to differentiate lesions of dental caries from tooth structure.The present study was undertaken to investigate the effects of contaminating saliva and blood on the numerical measurements generated by the system. The null hypothesis was that VistaCam scores would not differ from samples assessed in the dry state and when covered with saliva or blood.α = 0.05 and estimated β = 11.06 (study power = 88.94%). All teeth except those for group A2 were from adults aged 18 years or more and were examined under 20× magnification for pathology or defects. All teeth were carefully cleaned to remove external stains from the enamel. The sample groups comprised the following:A total of 112 extracted human teeth from the permanent dentition were collected with the approval of the institutional ethics committee (Reference No: 2003000040) from a dental school exodontia clinic. A power analysis was undertaken to determine sample sizes in the various groups, based on data from a pilot study. The power analysis assumed Group A1. Ten premolar teeth from patients aged over 17 years free of plaque, caries and other defects, which had been removed for orthodontic reasons. These were stored in highly diluted sodium hypochorite solution  to prevent any bacterial growth occurring on the samples.Group A2. Ten premolar teeth from teenage patients aged 17 years or less, free of deposits or disease. These were stored in the same manner as for Group A1.Group B1. Twenty teeth with large coronal cavities where the carious dentine was darkly coloured (dark brown or black). These were stored in distilled water saturated with thymol.Group B2. Twenty teeth with large coronal cavities where the carious dentine was not different in colour from sound dentine. These were stored in distilled water saturated with thymol;Group C1. Twenty teeth with thick deposits of plaque already present on a sound root surface, stored in stimulated human saliva diluted 1:10 in distilled water.Group C2. Twenty teeth with thick deposits of plaque already present on a sound enamel surface, stored in stimulated human saliva diluted 1:10 in distilled water.Group D. Five teeth with banded staining of the roots resulting from the use of tetracycline (confirmed by ultraviolet fluorescence examination of the teeth), stored in distilled water with thymol.Group E. Seven premolar and incisor teeth that had undergone root canal treatment and had been obturated with gutta percha and AH26® epoxy resin sealer , and had darkly stained crowns and roots, and had been stored in distilled water with thymol.The VistaCam intra‐oral camera was connected via USB to a laptop computer, and the manufacturer's supplied spacer was applied to give consistent position and angulation. The system was used in a dark room to avoid the influence of extraneous light. Each sample was assessed by one examiner in the moist state (without surface water). The image under 405 nm wavelength violet light excitation was recorded and analyzed using the supplied Dürr DBSWIN software, to generate a pseudoreference image, which provided the maximum numerical digital data which were used for subsequent analysis.To assess the influence of surface factors, normal and pseudoreference images were retaken after covering the samples with 40 μL volumes of human stimulated saliva from a single healthy male volunteer, and then after rinsing this away, with the same volume of heparinized anticoagulated human blood obtained from the same volunteer (diluted 1:8 in distilled water). This was intended to replicate the effect of gingival bleeding, which could occur under clinical conditions, giving contamination of the tooth surfaces by saliva mixed with small amounts of blood.The VistaCam numerical scores from the processed pseudoreference images were recorded, and GraphPad Prism  version 6 statistical software used to compare sample types, under different conditions . Data sets were assessed for normality. A repeated measures one‐way parametric analysis of variance was used to analyze differences between the dry state and the saliva wet state and blood covered state. As the primary purpose of the device is as a caries diagnostic adjunct, light and darkly stained carious dentine groups were then compared to other sample types. The Kruskall–Wallis test was used for comparisons between sample types under the same surface conditions.Mean VistaCam scores from samples are shown in Figure There were no statistically significant differences between dry and saliva‐coated surfaces. Thus, in relation to saliva coating, the null hypothesis was accepted.In contrast, the presence of blood generated fluorescence, which significantly elevated the originally low scores for healthy and plaque‐covered enamel and dentine, and for discoloured roots, compared to the same materials in a dry state or when coated with saliva, as it has shown this negative red blood imaging for one of the tooth samples covered with plaque in Figure Sample types that already had high scores in the dry state  did not show significantly elevated scores when blood was present.P > 0.05), and both were significantly higher than those for sound dentine (0.9–1), sound enamel (0.9–1.1), dental plaque on enamel (1–1.1) or roots (0.9–1), tetracycline stained (1.1–1.4) and root treated discoloured teeth (1–1.2). Regions of dental caries gave scores up to 2.2, whilst noncarious samples consistently gave scores in the range of 0.9–1.2  over sound roots and roots covered with dental plaque, and the same pattern was seen for sound enamel and enamel with dental plaque. Because of greater inherent sample fluorescence in all samples other than dentine surfaces covered with plaque, the presence of blood elevated the scores, but the gain was not statistically significant (P > 0.05).For dry and saliva coated samples, both dark caries and light caries gave significantly elevated scores  Walsh  does notThe digital scores generated by the VistaCam were found to be similar for lesions of dentine caries, regardless of whether they were coloured light or dark. As all the carious lesions in the study had frank surface cavitation, so would have been identified by a competent dental professional during a clinical examination using a mirror and dental probe. Scores for tetracycline teeth were high despite the absence of caries. This stresses the point that high scores for fluorescence on teeth may be caused by factors other than dental caries.The use of fluorescence‐based methods using violet light combined with a red filter to aiding the identification of infected dentine within cavitated dental caries has been an established method for many years  and Australian Dental Research Foundation (ADRF). The study was not funded by the manufacturer of the VistaCam system used in the investigation.


These results indicate that the dose per monitor‐unit calculations performed by the treatment‐planning system can be confidently utilized in the fulfillment of clinical dose prescriptions.This report specifically describes the use of a unique anthropomorphic breast phantom to validate the accuracy of three‐dimensional dose calculations performed by a commercial treatment‐planning system for intact‐breast tangential irradiation. The accuracy of monitor‐unit calculations has been corroborated using ionization chamber measurements made in this phantom. Measured doses have been compared to those calculated from a variety of treatment plans. The treatment plans utilized a 6‐MV x‐ray beam and incorporated a variety of field configurations and wedge combinations. Dose measurements at several clinically relevant points within the breast phantom have confirmed the accuracy of calculated doses generated from the variety of treatment plans. Overall agreement between measurements and calculations averaged PACS number(s): 87.53.–j, 87.66.–a During commissioning of a treatment‐planning system, calculations from the system are verified against either measurements or “hand calculations” performed for a series of configurations designed to represent clinical situations.et al.,et al.,Since current treatment‐planning algorithms now explicitly account for the 3‐dimensional (3D) volume of irradiated tissue, it is necessary to verify dose calculations performed in geometries significantly different than that of a water phantom. One such geometry is that of the intact breast irradiated tangentially. Leszczynski and DunscombeThe verification of dose calculations in 3D treatment planning of the breast has particular importance because tangential breast irradiation presents several challenging dosimetric conditions. The volume of irradiated breast is significantly smaller than most other clinical volumes. Dose normalization points are often located either close to beam edges or to tissue boundaries, and beams are often obliquely incident. Corrections for tangential‐field “flash” or “fall off” do not fully account for the total reduction in volume.In this work, the accuracy of absolute homogenous dose calculations performed by the ADAC PinnacleMeasurements of ionization were made in an anthropomorphic breast water phantom  that was3 waterproof ion chamber. The sleeve was constructed by machining an acrylic tube to make its interior dimensions match the exterior dimensions of a Physikalisch‐Technische Werkstatatten (PTW) Model N233642 ion chamber . The wall of the sleeve was 2.7 mm thick. The sleeve is mounted onto a base that can then be attached to the flat back of the phantom. This permits the ion chamber to be inserted from below. The assembly has been designed to allow the ion chamber to be placed at any point along a perpendicular bisector located at the midpoint of the line connecting the posterior borders of the medial and lateral tangential fields. The position of the chamber along the bisecting line is localized using a polystyrene rod with dimensions equal to those of the ion chamber. Position markers, consisting of 1 mm diameter holes drilled through the localization rod, are located along the length of the rod in 7 mm (the length of the chamber's sensitive volume) increments. The chamber‐localization device allows high‐contrast visualization, during CT imaging of the phantom, of possible chamber measurement positions . For CT data acquisition, the phantom, with chamber positioning device, was placed in treatment position and a full scan was performed. Three treatment isocenters were chosen and localized along the perpendicular bisector of the line between the posterior edges of the medial and lateral tangential fields. A first point was centrally located within the impression of the breast. A second point corresponded to the National Surgical Adjuvant Breast and Bowel Project (NSABP) calculation point: a point located two‐thirds of the distance from the apex of the breast to the posterior edge of the tangential fields. A third point was located at a nominal 2.0 cm distance from the posterior field edge. The first two isocenters are believed to be representative of those that are commonly used clinically (mid‐breast and NSABP); the third was placed near the field edge to test an extreme case that is not uncommonly encountered. The location of these points is shown in The phantom underwent “virtual simulation” for each isocenter position using the proposed field borders marked on the breast phantom. In all cases, gantry angles were set such that the divergence of each beam matched posteriorly. Collimator angles were determined using the field border wires to match the field edge to the wire. The field sizes were chosen to match the field borders and to give approximately 2 cm of fall off or flash beyond the breast tissue.Treatment plans using 6 MV beams were developed for each isocenter position using the ADAC PinnacleIn each plan, 200 cGy was delivered to isocenter. The contribution of each field to the total dose at each measurement point is presented in 10×10 cm2 field, 100 cm. Source to Surface distance (SSD), and a depth of dmax in water, with a system of known calibration. Chamber readings, during both calibration and experiment, were corrected for temperature and pressure, to account for possible differences between calibration and experiment conditions.The phantom and ion chamber assembly were irradiated utilizing the 6‐MV x‐ray beam of a Siemens Mevatron 6740 MXE linear accelerator . Ionization was measured with a PTW N, 233642 ionization chamber and a CNMC Model 206 electrometer . Prior to phantom irradiation, the chamber/electrometer response per unit dose was determined by cross comparison using a For each phantom irradiation, the chamber was placed at its first measurement position and the first isocenter was set. SSD's were verified for both medial and lateral fields. The first set of tangential fields were then treated using the monitor units calculated by the Pinnacle.Ionization measurements made over two evenings demonstrated a precision better than 0.2% (coefficient of variation).The distribution of the measured to calculated ratios can be seen in the histogram of ,The dose‐calculation verification measurements performed in this study utilizing an anthropomorphic breast phantom clearly demonstrate absolute homogenous dose calculation accuracy – even in the case of tangential irradiation of the breast. This high degree of accuracy is achievable when a treatment‐planning system and its beam data are appropriately modeled and commissioned.,et al.,Our breast phantom results are in good agreement with previously published results for conventional phantomset al. have evaluated uniform dose distributions, we have evaluated both uniform dose distributions, as well as fields producing dose gradients within the irradiated volume.Whereas Baird et al.,In their report, Loshek (0.998±0.009), with calculations performed under a variety of treatment field configurations. The accuracy of point homogeneous dose calculations along an axis perpendicular to the edges of divergence‐matched tangents at mid‐separation, produced by a 3D system during intact‐breast treatment planning, has been confirmed. These results, coupled with those of Baird et al.,Measurements of dose made in a fairly unique anthropomorphic breast phantom have demonstrated excellent agreement for 6‐MV x‐ray beams The authors would like express their appreciation to Jens Boving and Mark Bushman of the Department of Radiation Physics Instrument Shop for their expert craftsmanship in producing a phantom of great utility and excellent quality. Without their dedication, this work would not have been possible.


IUCN) Red listed birds found in the study area was examined. A machine learning algorithm, MaxEnt, was used in conjunction with these data and field collected geographical locations of the avian species to identify the factors influencing habitat preference of the different bird species and their suitable habitats. Results show that distance from different forest patches played a more important role in influencing habitat suitability for the different avian species than local scale factors related to vegetation structure and health. In addition to distance from forest patches, LiDAR‐derived forest structure and Landsat‐derived spectral variables were important determinants of avian habitat preference. The models derived using MaxEnt were used to create an overall habitat suitability map (HSM) which mapped the most suitable habitat patches for sustaining all the avian species. This work also provides insight that retention of forest patches, including degraded and isolated forest patches in addition to large contiguous forest patches, can facilitate bird species retention within tropical agricultural landscapes. It also demonstrates the effective use of RS data in distinguishing between forests that have undergone varying levels of degradation and identifying the habitat preferences of different bird species. Practical conservation management planning endeavors can use such data for both landscape scale monitoring and habitat mapping.Avian species persistence in a forest patch is strongly related to the degree of isolation and size of a forest patch and the vegetation structure within a patch and its matrix are important predictors of bird habitat suitability. A combination of space‐borne optical (Landsat), ALOS‐PALSAR (radar), and airborne Light Detection and Ranging (LiDAR) data was used for assessing variation in forest structure across forest patches that had undergone different levels of forest degradation in a logged forest—agricultural landscape in Southern Laos. The efficacy of different remote sensing (RS) data sources in distinguishing forest patches that had different seizes, configurations, and vegetation structure was examined. These data were found to be sensitive to the varying levels of degradation of the different patch categories. Additionally, the role of local scale forest structure variables (characterized using the different RS data and patch area) and landscape variables (characterized by distance from different forest patches) in influencing habitat preferences of International Union for Conservation of Nature ( Although the use of LiDAR has been known to be costly , landscape scale factors in form of distance from forest patches have been included as this may influence species persistence in an agricultural landscape ; (B) small forest patches with large canopy gaps, thick understory, and presence of many small trees. These were mostly found in the vicinity of villages (mean size: 0.38 km2); (C) small patches of closed canopy forest. The presence of some understory and several small trees was detected in these. These were located within woodlands or scrublands that had been heavily exploited for timber (mean size: 0.11 km2); and (D) highly degraded forest patches with an open canopy and scrub development (mean size: 0.31 km2). These different forest patches were then manually digitized on Google Earth.The area is a landscape of agricultural fields and patches of tropical woodland of varying sizes, configurations, and disturbance histories. Some of the patches continue to be exploited for timber. These patches have been categorized into different categories (A–D) on the basis of size, configuration, and the qualitative assessment of forest degradation. Local experts were employed to locate different forest patches and help categorize them qualitatively based on their structure, configuration/size, and magnitude of degradation and intactness. Using qualitative forest quality assessment indicators previously used by Turner et al. , we examBird surveys were carried out in December 2015 with the assistance of a local forestry official in at least three patches from each of the categories, spanning as much of the production forest as possible, using a point count method. This method is useful for getting a spatially representative sample from each patch  only. TerraScan was used for data preprocessing and initial point classification  was used with a 30‐m field of view (FOV), delivering a point density of 1 point/mThe avian geo‐location data were collected in 2015. The forest change is assumed to be low as no forest clearance activity has occurred in the study area; hence, it is appropriate to compare these data. Earlier works suggest that a time lag of 6 years or more between LiDAR and field data collection has no impact on patterns of avian distribution in relatively undisturbed forests  as follows . An enhanced Lee filter was applied to reduce speckle, while retaining the image texture using ENVI. HH and HV values were used to calculate the Radar Forest Degradation Index (RFDI), a radar‐derived measure of forest degradation . These were in turn put through the 6S atmospheric correction module provided by ClasLite to produce top of the atmosphere surface reflectance   were evaluated as part of this research. Vertical vegetation parameters (derived from LiDAR) varied significantly among the four patch categories Figure a,b.p < .01). The average canopy height was found to be significantly different across all four patch categories while the standard deviation of height only varied significantly between patch categories A and B. Large forest patches (A) had the highest median value of these variables. Large forest patches (A) also had significantly different values in all the percentile height bins compared with the smaller patches (B–D): p10  and p90  as shown in Figure The average height, as well as the standard deviation height differed among the four patch types , indicating greater canopy intactness and structural complexity compared with small isolated patches (B) and highly degraded forest patches (D)  and small patches within a matrix of degraded forests (C) had significantly higher canopy cover  Figure e,f.p < .01), indicating the presence of a relatively closed canopy structure and reduced understory compared to other patch configurations. Patch A had also a significantly lower ALOS PALSAR RFDI value compared with other forest patch classes, indicating low rate of forest degradation and anthropogenic disturbance  compared to the other forest patches . Patch category A (followed by patch category C) has the highest values of greenness and wetness  and small close‐canopied forest patches (C) had lower values of RFDI than patch categories (B) and (D), indicating that they were less degraded  and (C) have significantly higher values of Landsat‐derived wetness and greenness, indicating higher levels of photosynthetically active and low levels of degraded vegetation. Further the values of greenness varied significantly across all four patch categories and wetness varied significantly between all patch categories except between (A) and (C).3.2Two MaxEnt models were developed. In the first model, only the local scale forest structure variables  were modeled. The AUC of SDMs for all species  was >0.7. The percentage contribution of each of the local scale factors in explaining habitat suitability of individual species is presented in Table In addition to LiDAR structural variables, Landsat‐derived variables of canopy spectral properties such as greenness also influence habitat suitability for different avian species at local scale. Landsat‐derived spectral metrics are important explanatory variables along with LiDAR‐derived structural variables.In the second model, we included both local scale forest structure variables and landscape factors (Euclidean distances between bird species presence and the four different forest patches). The AUC of all the SDMs (except for green peafowl and red collared woodpecker) was >0.7. For all the cases with AUC > 0.7, the landscape scale factors (distance from different forest patches) had higher percentage contribution to habitat suitability models of individual bird species than local scale factors Table .The species habitats were also found to moderately overlap with Schoener's D index ranging from 0.1 to <0.7 Table . A D indJackknife test of variable importance also revealed that distance of different patches had more information by themselves as compared to local forest structure variables  unsuitable, (2) marginal habitat, and (3) highly suitable habitat using the thresholding scheme recommended by Nazeri et al.  Analysis4This study had two overarching aims. First was to evaluate the ability of different RS metrics to distinguish between forest patches that have faced different levels of degradation and have different sizes and configurations. Second was to identify suitable habitats for avian species in a tropical forest–agricultural ecosystem. Section 4.1Large forest patches were distinctly different in structure to the small patches. The tallest forest was found in the large forest patches . A detailed analysis of tree species within the different patch types is outside the scope of this research, but it may be inferred that these large patches still retains tall Dipterocarp tree species, which once dominated much of the lowland ecosystem in the Greater Mekong region and can reach heights of up to 40 m  varied significantly across all four patch categories. The patch categories were determined on the basis of qualitative field assessments carried out by local experts. These findings indicate that derived qualitative assessments too can help in characterizing forest and other land use types. This has potential conservation ramifications. Conventionally, forest types in tropical Asia are classified on the basis of ecological classifications such as those suggested by Whitmore  using a combination of field collected data, multiple RS data for characterizing forest structure, and landscape variables. Indeed, MaxEnt has been used for modeling species distribution and identifying factors influencing habitat suitability in a number of tropical forest ecosystems  pertaining to forest structure and health . Research by Chang, Quan, and Wang  and FlasOur research was conducted in a production forest in Laos. The tropical forest–agricultural matrix found here is a microcosm of tropical landscapes in the majority of the Greater Mekong region. Hence, it is important to devise strategies that can help with biodiversity retention in human‐modified landscapes and allow for landscape scale monitoring of forest degradation. The role large contiguous forest patches can play in bird species conservation has been well established, and it has been recommended that retention of large forest patches can help maintain a diverse species assemblage in human‐modified ecosystems , and Landsat‐derived variables are also useful indicators of habitat preference. Given that LiDAR data are expensive, future research could focus on using a combination of landscape scale variables along with Landsat‐derived metrics for identifying suitable habitats in areas that do not have LiDAR coverage.5This research has demonstrated how a combination of optical, radar, and LiDAR data may be used for assessing forest degradation and variation in forest structure across varying disturbance regimes/patch configurations. This is of potential importance in postconflict countries such as Laos which are rich in tropical forests. These countries face an ongoing problem of the presence of unexploded landmines and shells, which makes the collection of field data extremely hazardous. As this work demonstrates, RS data from different sources can be employed for rapid conservation monitoring by facilitating landscape scale identification of forest structure patterns and suitable habitats. Data from multiple sensors are useful for identifying the factors that influence avian habitat preference in a tropical forest–agricultural matrix ecosystem. Our findings make a case for promoting the retention of forest patches that includes degraded forest patches within an agricultural ecosystem for bird species conservation.The authors have no conflicts of interest to declare.MS collected the field data, analyzed the data, and wrote the manuscript. TT, ZH, and CN provided suggestions on manuscript improvement. TT and ZH provided information about the study site and CN advised on ALOS PALSAR data processing Click here for additional data file. Click here for additional data file.