Plasmon-enhanced Raman spectroscopic metrics were developed for in situ quantitative and dynamic assays of viable, apoptotic and necrotic cells. In situ, quantitatively and dynamically monitoring such processes may provide vitally important information for cell studies. However, such a method still remains elusive, even though current immunochemical methodologies have developed extremely valuable tools. Herein, we demonstrate Raman spectroscopic metrics for validating and quantifying apoptotic and necrotic cells based on their distinct molecular vibrational fingerprints. It not only allows us to quantify apoptotic and necrotic cell populations in situ in adherent cell samples, but also to be capable of continuously monitoring the dynamical processes of apoptosis and necrosis at the same time in one sample. This method provides comparable results with the “gold standard” of flow cytometry, moreover, with several incomparable advantages. Our work offers a powerful new tool for cell apoptosis and necrosis assays and is expected to become a benchmark technology in biological and medical studies.Apoptosis and necrosis are distinct cell death processes related to many cellular pathways.  However, in situ, quantitatively and dynamically monitoring such different cell death processes still remains a great challenge. For instance, flow cytometry requires suspending cells in a stream of fluid, thus it is not available for in situ testing of adherent cells and it cannot follow dynamics on the same cell sample. Microscopic imaging based on immunofluorescence is capable of in situ validation of apoptotic or necrotic cells; however, it is still hard to provide high-throughput quantitative data using current microscopy techniques in the way that flow cytometry does. Other molecular biological methodologies such as DNA electrophoresis, Western blotting and enzyme colorimetric assays are also not capable of in situ testing of living cells since such methods require collecting molecules from cell lysis.11Cell apoptosis and necrosis are very critical biological processes related to many fields of biological and medical research.20 As a non-invasive optical technique, Raman spectroscopy allows continuous analysis of chemical information inside living cells.21 Various techniques, including coherent anti-Stokes Raman spectroscopy (CARS),23 stimulated Raman spectroscopy (SRS),16 and tip or surface-enhanced Raman spectroscopy (TERS or SERS)29 have been developed. Particularly, combined with the targeting ability of bio-conjugated plasmonic nanoparticles, the spectral features from specific regions (e.g. the nucleus) of single living cells can be detected by plasmonic-enhanced Raman spectroscopy (PERS),34 which enable the monitoring of molecular events during the cell cycle,36 cell apoptosis38 and intracellular drug action,40 at the single-cell level. However, single-cell based Raman spectroscopy collects the spectrum of one cell at a time. Since Raman scattering from a single cell is mostly weaker than fluorescence, it thus requires a much longer time to integrate the signals. Such distinct limitations were considered to be the main hurdle for single-cell Raman spectroscopy to achieving high-throughput screening. Collecting the mixed spectra of a large number of cells simultaneously would definitely increase the throughput, however; extracting and quantitating the spectral features from multi-component samples became another challenge. Fortunately, it was possible to address such challenges by applying chemometric methods, such as principal component analysis (PCA)41 and so on.Over the past decades, Raman spectroscopy has been intensively explored for the investigation of molecular constitutions within cells.in situ quantitative and dynamic assay of apoptotic and necrotic cells based on measuring their distinct molecular signatures. Through analyzing the PERS spectra from the biomolecules at the cell nucleus, the correlated Raman bands of viable, apoptotic and necrotic cells were identified and different cell populations were clearly discriminated. We then developed a mathematical model to calculate the percentage of viable, apoptotic and necrotic cell populations from the averaged PERS spectra of adherent cell samples. This strategy not only allows in situ quantitative testing of apoptotic and necrotic cells, but is also capable of monitoring the dynamic apoptotic and necrotic processes in the same cell sample over a different period of time. Compared to the current “gold standard” flow cytometry, our PERS strategy could provide pretty consistent results, with an average difference of 2.86%, moreover, it has several incomparable advantages. Firstly, it works for an adherent cell sample. Secondly, it allows in situ measurement of living cells. Thirdly, it enables the study of the dynamics of cell death in real time. This technique provides a new tool for in situ, quantitative and dynamic analysis of cell apoptosis and necrosis directly in adherent cell samples, which may promote cell analysis applications in many fields.Herein, combining PERS and chemometrics together, we present a Raman metric strategy for an via a citrate-reduction approach, and were further conjugated with methyl polyethylene glycol (mPEG), arginine–glycine–aspartic acid (RGD) and nuclear localization signal (NLS). These NT-AuNSs were about 20 ± 4 nm in diameter (44 The red scattering from aggregates (i.e. coupling modes) mixed with the green scattering from individual particles (i.e. single-dipole mode), exhibited a bright “golden” color under the DF microscope  were collected, which significantly extended the possibility of reaching high-throughput screening. The presence of NT-AuNSs enhanced the Raman signals of cells ∼104 fold, but none of the Raman bands of the NT-AuNSs appear as strong bands in the cell spectrum . The NT-AuNSs were synthesized diameter . They hadiameter  in solutdiameter . Once thdiameter , their pdiameter , due to croscope . Such a croscope . The lascroscope . This cospectrum . The spespectrum , to make38 as well as in our current study /tyrosine,54 phenylalanine ring breathing,55 peptide bonds (C–N)59 and protein amide III band,60 respectively.We firstly carried out a set of control experiments to create spectroscopic references of viable, apoptotic and necrotic cells, using HSC-3 cells as a model (see Methods section for details). All cell samples were pretreated with NT-AuNSs for 24 h at a minimum concentration of 0.05 nM, which has been proven to scarcely affect cell viability in the previous literatureB, ESI–1 , which c–1 decrease, while the bands at 1000–1020 and 1200–1240 cm–1 increase. The disulfide (S–S) bonds and C–S bonds play an important role in the folding and stability of protein native structure.62 In apoptotic cells, the decrease of the S–S band indicates disulfide bond breakage within intracellular proteins when they undergo denaturation.63 The parallel increase in the 1000–1020 and 1200–1240 cm–1 bands also indicates protein denaturation as these bands originate from the ring breathing of phenylalanine, β-pleated sheet conformation or C–C6–H5 stretching of phenylalanine and tryptophan, which are no longer positioned within the interior of a folded protein.62 Secondly, a pronounced decrease in the intensities of the 1120–1140 and 1280–1320 cm–1 bands was also seen after apoptotic treatment. Since these two bands are attributed to protein peptide bond (C–N) stretching and α-helix protein structure, thus here, the decrease of these vibration bands indicates that the peptide bond hydrolyses during nuclear protein degradation.66 Thirdly, the band intensity at 820–860 cm–1 decreases while that of the 1560–1600 cm–1 band increases. These two bands could be attributed to the DNA O–P–O backbone and ring mode of guanine and adenine, respectively.59 These vibrational changes indicate DNA backbone breakage and the exposure of purine bases, which correlates with nuclear DNA fragmentation as a result of cell apoptosis.67 All of the above Raman vibrational changes indicate the occurrence of protein denaturation, protein degradation and DNA fragmentation, which are typical molecular events of cell apoptosis.52Apoptotic cells have several notable spectroscopic changes compared to viable cells . Firstly–1 also decreases in necrotic cells, indicating the breakage of disulfide bonds in the protein tertiary structure. However, the peptide bond vibration at 1120–1140 cm–1 did not decrease as much as in apoptotic cells, and the phenylalanine band at 1000 cm–1 also did not increase so much. The above results indicate that the breakage of disulfide bonds indeed occurs in apoptotic cells, but protein degradation is not as notable as in apoptotic cells. The probable reason is that, for necrotic cells, cell death occurs rapidly, and the structure of enzymes was also damaged in short time, thus the protein cannot undergo proteolysis since there is a lack of active enzymes. Thereby, the necrotic cells do not show as much change in the 1000 cm–1 phenylalanine band and 1120–1140 cm–1 peptide bond vibration band as apoptotic cells do. The decrease in the intensity of the DNA backbone band at 820–860 cm–1 and the increase of the 1560–1600 cm–1 band intensity exhibits a similar trend as with the apoptotic cells, which indicates the occurrence of DNA fragmentation after necrotic treatment. In addition to the above changes, the most notable change is the increase of lipid or protein CH2/CH3 deformation and bending band around the 1460–1500 cm–1 region.68 The strong lipid vibration in necrotic cells could be attributed to the damage of cell membranes and intracellular vessel structures, thus the NT-AuNSs are no longer located around the cell nucleus and thereby may have got in contact with the cellular membrane and enhanced the lipid signals.The Raman features of necrotic cells are different from those of apoptotic cells . Compare–1 and PC2 loading shows peaks at 500, 1000, 1180, 1210 and 1585 cm–1. We also did a difference analysis on the representative Raman features to reveal their correlation to each cell population (see Methods section for details). The representative viable, apoptotic and necrotic features after difference analysis treatment are shown in Fig. S5 in the ESI,Even though we have seen that the viable, apoptotic and necrotic cells exhibit different PERS spectroscopic features, it is still not easy to pick up the most significant differences between each cell population. To address this problem, we utilized principal component analysis (PCA), a chemometric method suitable for extracting principal information from multidimensional data sets. –1 to represent the viable, apoptotic and necrotic cell populations, respectively. We then developed a mathematical model to calculate the percentage of viable, apoptotic and necrotic cell populations from the averaged PERS spectra of any given samples. Three ideal samples are assumed, which contain 100% viable cells, 100% apoptotic cells and 100% necrotic cells, named Svia, Sapo and Snec. The intensity of characterized Raman bands for these ideal samples are represented by Ik)viaaponecvia( × x% + Ik)apo( × y% + Ik)nec( × z% = Ik)mix(where Ik)mix% + Ibackground = Ireferencewhere Iideal is the theoretical band intensity of the ideal samples, Ireference is the experimentally observed band intensity of the reference samples in the current work, % is the percentage of viable, apoptotic and necrotic cells in experimental reference samples, and Ibackground is the intensity of nonspecific background at specific wavenumbers.As mentioned before, the three reference samples used in the current work were experimentally created, and the percentages of viable, apoptotic and necrotic cells were 94.02%, 93.42% and 92.16%, respectively. Since such reference samples are actually not 100% ideal samples, so the Raman band intensity of the above reference samples are not exactly the same as the ideal theoretical samples. To obtain more accurate calculation results, we did a correction on the Raman band intensity of the experimental reference samples by using a linear equation:Iideal of the bands at 500, 1000 and 1500 cm–1, we calculated the percentage of viable, apoptotic and necrotic cell populations. As a proof of concept, we tested this method on two adherent cultured cell lines (HSC-3 and MCF-7 cells), under the treatment of four types of anticancer drugs; cisplatin (CisPt), fluorouracil (5-FU), camptothecin (CAMP) and doxorubicin (DOX).Using the above equation and the corrected in situ at 1, 4, 8 and 12 hours of drug treatment  as models. These two types of cells exhibit very similar PERS spectroscopic features when they are treated using the same viable, apoptotic and necrotic procedures for creating reference samples  water via centrifugation at 6000 rpm for 15 min. For PEGylation, a 1.0 mM solution of thiol-modified methoxypolyethylene glycol  was added to a AuNSs solution with a final molar ratio of 1000 : 1. The PEG–AuNSs solution was incubated for 24 hours, and then centrifuged at 6000 rpm for 15 min and washed with DI water. After PEG modification, the AuNSs were conjugated with RGD and NLS peptides by the addition of a 5.0 mM RGD (CGPDGRDGRDGRDGR) peptide solution and a 5.0 mM NLS (GGVKRKKKPGGC) peptide solution to PEG–AuNSs with a molar excess of 104 and 105, respectively. The RGD/NLS–AuNSs were purified by centrifugation  to remove unbound ligands. The final obtained nuclear-targeting AuNSs were termed NT-AuNSs.Gold nanospheres (AuNSs) were synthesized using a citrate-reduction based approach,2 humidified incubator. For PERS experiments, the cells were cultured in a 96-well culture plate and pretreated with 0.05 nM NT-AuNSs for 24 hours before collecting spectra.Human oral squamous cell carcinoma (HSC-3) and human breast adenocarcinoma (MCF-7) cells were cultured in Dulbecco's Modified Eagle's Medium , supplemented with 10% fetal bovine serum  and 1% antimycotic solution (Mediatech), in a 37 °C and 5% CO2O2 treatment for 24 h, and the reference necrotic cells were treated in boiling water (100 °C) for 10 min. The viable, apoptotic and necrotic cells were evaluated by flow cytometry using a standard Annexin V-FITC and PI double staining procedure.The reference viable cells are control cells without any treatment except for 0.05 nM NT-AuNSs pretreatment; the reference apoptotic cells were induced by 100 μM Hin situ dynamic PERS measurement, the stage and culture plate were covered with a homemade case with a temperature control unit and an access to inject 5% CO2 to keep the cells alive. For each group, spectra from 10 wells of cells were taken to get an average result, and at least 3 independent trials were taken for all experiments.The PERS experiments were carried out on a lab-built Raman plate reader setup  staining was used to confirm the results of PERS spectroscopy. For this measurement, cells were grown in 12-well culture plates and pretreated with 0.05 nM NLS/RGD–AuNSs for 24 h before any drug treatment. After drug treatments, cells were collected after trypsinization and washed with cold DPBS. Then, cells were redispersed in binding buffer, and 5 μL of Annexin V-FITC and 2 μL of propidium iodide (PI) were added. Cell solutions were then incubated for 15 min at room temperature and run on a BD flow cytometer by using standard FITC and PI channels. Viable, apoptotic and necrotic cell populations were analyzed using FlowJo software.via Matlab R2015b. Before running PCA, 20 spectra from each group  were randomly selected and normalized from 0 to 1. Scatter plots of PC1 and PC2 scores were utilized to classify different cell populations. A Kernel density estimation method is used to smooth the diagram of scores to generate a 1D intensity distribution. PC1 and PC2 loading exhibited the discrimination weight between different cell groups at certain Raman shifts. To address this, three Raman spectra were randomly selected from each of the three cell groups, and a PC loading curve was calculated by running PCA on these three spectra. This calculation process was carried out 20 times to get the average value (black line) and standard deviation (highlighted as red color) of all 20 PC loadings.PCA is a suitable tool for extracting principal information from multidimensional data sets such as Raman spectra. In the current study, the PC scores and loadings were calculated –1 gave the best calculation results in our current system.The percentage of cell apoptosis and necrosis were calculated according to the linear equation sets proposed in the current work. The equations were solved by using Mathematic software, the algorithm was trained by inputting the reference data of cell apoptosis and necrosis obtained by flow cytometry, and a self-consistent calculation strategy was used to get a convergent numerical solution. Calculations were tried according to the normalized intensity of different bands (Fig. S6 and S7, ESI


The compound eyes of insects allow them to catch photons and convert the energy into electric signals. All compound eyes consist of numerous ommatidia, each comprising a fixed number of photoreceptors. Different ommatidial types are characterized by a specific set of photoreceptors differing in spectral sensitivity. In honey bees, males and females possess different ommatidial types forming distinct retinal mosaics. However, data are lacking on retinal ontogeny and the mechanisms by which the eyes are patterned. In this study, we investigated the intrinsic temporal and circadian expression patterns of the opsins that give rise to the ultraviolet, blue and green sensitive photoreceptors, as well as the morphological maturation of the retina during pupal development of honey bees.UVop) and only marginal levels of blue (BLop) and green (Lop1) opsin mRNA. In the second half of pupation, when photoreceptors and rhabdoms elongate, opsin expression in workers becomes dominated by Lop1 mRNA. In contrast, the dorsal drone eye shows high expression levels of UVop and BLop mRNA, whereas Lop1 mRNA level decreases. Interestingly, opsin expression levels increase up to 22-fold during early adult life. We also found evidence that opsin expression in adult bees is under the control of the endogenous clock.qPCR and histological labeling revealed that temporal opsin mRNA expression differs between sexes and correlates with rhabdom elongation during photoreceptor development. In the first half of the pupal stage, when the rhabdoms of the photoreceptors are still short, worker and  drone retinae exhibit similar expression patterns with relatively high levels of UV (Drosophila, where the highest expression levels are found during the late pupal stage and remain constant in adults. From an evolutionary perspective, we hypothesize that the delayed retinal maturation during the early adult phase is linked to the delayed transition from indoor to outdoor activities in bees, when vision becomes important.Our data indicate that the formation of the sex-specific retinal composition of photoreceptors takes place during the second half of the pupal development, and that opsin mRNA expression levels continue to increase in young bees, which stands in contrast to  Detecting and processing light is crucial for the survival and reproduction of nearly all animals. Aside from various forms of vision, the perception of light is important for entraining the endogenous clock. Insects represent one of the most diverse groups of the animal kingdom and have colonized almost all habitats; they usually possess a pair of compound eyes that converts photon energy into an electric signal for further processing , 2. The In a wide range of animal species, it has been shown that different photoreceptor types, which are characterized by a distinct spectral sensitivity and a related opsin protein, form random mosaics, localized zones or bands within the retina , 10. In Apis mellifera), which is recognized as an insect model for visual (color) perception, learning and memory [Retinal mosaics and distinct photoreceptor distributions are suggested to be present in the compound eyes of workers and drones of the honey bee , BLop  and Lop1  exhibited a similar oscillation pattern for 24 h  imaging data. Rhabdom length and diameter significantly increased during pupal development from ca. 13 μm length in 1-day old pupae to ca. 300 μm in adult bees, and from ca. 2 μm in diameter in 1-day old pupae to ca. 5 μm in adult bees . Larval and pupal development of the Western honey bee takes place inside the nest under constant darkness [Drosophila, Rh1 opsin gene expression is essential for correct rhabdomere development [In the present study, we showed that three opsin genes, nt Figs. . At earlRNA Fig. , which cses Fig. , which ases Fig. . Surprisdarkness  and thusdarkness . Furtherdarkness . In Droselopment , and simBLop mRNA expression commences early in workers (P1-2) but much later in drones (P5). In contrast, Lop1 mRNA expression starts approximately at mid-pupation (P4-5) in both sexes. Interestingly, physiological studies have found no green-sensitive photoreceptors in the dorsal eye of adult drones [Lop1 mRNA is expressed by the end of the pupal phase. Since we observed only low Lop1 mRNA expression levels during pupation, and the relative proportion of Lop1 mRNA expression obviously decreases during adolescent development, regulatory post-transcriptional processes [Lop1 mRNA or protein in adult drones, which may explain the lack of green photoreceptor cells in the dorsal part of the adult drone eye. Alternatively, Lop1 mRNA is only transiently expressed in dorsal drone eyes and never translated into protein, as recently been suggested for the PxG2 opsin in some photoreceptors of the type I and II ommatidia during retinal development of the butterfly Papilio xuthus [t drones , 22, wherocesses  could leo xuthus . Since io xuthus . Thus, fDrosophila. Whereas in honey bees, opsin expression and rhabdom maturation co-occur, opsin expression in flies is initiated much later near the end of the retina completion [Visual pigments are located in the fused rhabdom of the bees’ photoreceptor cells, which functions as a light guide to convey the photons from the periphery to the light-sensitive molecules , 6. Durimpletion , 36.Lop1 and arrestin mRNA in young in-hive bees compared to foragers [Drosophila are higher during the late pupal phase compared to adult flies [Based on our results, we hypothesize a two-step process in the development and differentiation of the honey bee compound eyes. During the first step, which takes place from mid to end of pupation, the photoreceptor cell meets its fate and the corresponding opsin is expressed. In addition, the rhabdoms increase in length and diameter, and absolute opsin expression level rises. In a second step, which takes place after eclosion, when the determination of photoreceptors has already been completed, the quantity of opsin mRNA in both workers and drones increases drastically. This upregulation of opsin expression suggests an early adult maturation phase which takes place during the first days after eclosion, when workers and drones remain in the dark hive and only gradually come into contact with light during the transition from nurses to foragers or during their first orientation flights , 38. Thiforagers . Moreoveforagers . Also, hforagers  and 1-daforagers . In contlt flies , which wLop1 gene by means of qPCR and northern blot analyses [All our samples were collected at the same time of the day, since it has been shown that opsin expression in insects (Noctuidae: ) and veranalyses , 45. We analyses  and restanalyses , matchinanalyses . As prevRetinal ontogeny differs between honey bee workers and drones. Our results clearly show a sex-specific and spectral type-specific onset of opsin expression, and further that opsin mRNA expression levels evidently coincide with rhabdom and photoreceptor development during the pupal phase in honey bees. Since opsin expression levels still increase in young bees, we hypothesize that the elongated retinal maturation during the adult phase became possible due to the delayed transition from indoor to outdoor activities in bees. Future studies comparing the retinal opsin expression pattern of social insect species characterized by an age polyethism (e.g. honey bees) with those exhibiting alloethism (e.g. bumble bees) will allow to verify this hypothesis. In summary, our study provides a first basis for future studies aiming to unravel the proximate mechanisms resulting in a retinal mosaic of the honey bee compound eye.Apis mellifera carnica were transferred from hives, located at the bee facility of the University of Würzburg, to the laboratory and were kept in an incubator at 34 °C and ~ 60% humidity at constant darkness. We identified eight pupal stages in workers  for 13 days and were kept in constant darkness on day 14. From these bees, individuals were collected at four-hour intervals over a time span of 24 h at day 14, adding up to six individuals per sampled time point . All collected pupae and adolescent bees were immediately transferred to liquid nitrogen and stored at − 80 °C until further processing.We removed both eyes  of workers since the different photoreceptor types seem to be approximately evenly distributed in the compound eye . In contUVop, blue-sensitive opsin, BLop, [Lop1 and Lop2 [Lop2 expression is restricted to the ocelli [Lop1 in the honey bee compound eye. As an internal control we used the Ribosomal protein 49 (Rp49) which has been previously shown to be a stable housekeeping gene in Apis mellifera [. Amplification efficiency for each primer pair was determined by means of a serial 1:10 dilution ranging from 101 to 106 copies  and rinsed them once for 10 min in PBS with 2% Triton-X 100 and twice in PBS with 0.2% Triton-X 100. Sections were then incubated in Alexa Fluor 488 Phalloidin  for 1 day at 4 °C to label f-actin. Sections were rinsed three times in PBS and subsequently incubated in Hoechst 34580  for 15 min at room temperature to label cell nuclei. Finally, sections were rinsed in PBS five times, transferred to 60% Glycerol in PBS for 30 min at room temperature and mounted in 80% glycerol in PBS on slides. To visualize the retinae, we used a confocal laser-scanning microscope  equipped with an argon/krypton and a three diode laser. Single images of sections were taken at a resolution of 1024 × 1024 pixels with a HC PL APO objective lens: 20/0.7 NA imm; with additional digital zoom: 2.0-4.0. Furthermore, scanned images were processed and edited in ImageJ 1.51e  and CorelDRAW Graphics Suite X7 .- ΔΔCT- method [Rp49 and the expression level of newly emerged bees . We calculated and estimated the relative proportions of opsin gene expression as followed:To evaluate the relative opsin expression, we used the 2- method , 54. Opsgene is defined as the expression of each individual opsin gene and Egene as the primer efficiency for the respective gene. CTgene depicts the mean threshold cycle determined during qPCR for each pupal stage (for more details see: [Whereby OEils see: ). Expres


The coatings also feature high mechanical, chemical and thermal stability, which is superior to all the reported colorful super anti-wetting coatings. Moreover, superamphiphobic coatings of different colors can be prepared via the same procedure using the other metal oxides instead of IOR. We believe the colorful superamphiphobic coatings may find applications in many fields like anti-climbing of oils and restoration of cultural relics, as the coatings are applicable onto various substrates.Colorful super anti-wetting coatings are receiving growing attention, but are challenging to invent. Here, we report a general method for preparing mechanically robust and thermally stable colorful superamphiphobic coatings. A composite of palygorskite (PAL) nanorods and iron oxide red (IOR) was prepared by solid-state grinding or hydrothermal reaction, which was then modified by hydrolytic condensation of silanes to form a suspension. Superamphiphobic coatings were prepared by spray-coating the suspension onto substrates. The superamphiphobicity depends upon the surface microstructure and chemical composition, which are controllable by the PAL/IOR concentration and the solid-state grinding time. The colorful coatings show excellent superamphiphobicity with high contact angles and low sliding angles for water and various organic liquids of low surface tension, e.g., toluene and  Great efforts have been made for preparing superamphiphobic coatings  could roll off. For the design of superamphiphobic coatings with low sliding angles (SAs), some special micro-/nanostructures   and tetraethoxysilane (TEOS) in the presence of the PAL/IOR composite. Finally, the PAL/IOR@fluoroPOS coatings were prepared by spray-coating the suspension onto substrates. The colorful coatings show excellent superamphiphobicity with high contact angles (CAs) and low SAs for water and various organic liquids of low surface tension. The colorful coatings also feature high mechanical, chemical and thermal stability up to 400°C.Here, we report a general method for preparing mechanically robust and thermally stable colorful superamphiphobic coatings by the combination of PAL nanorods, iron oxide red  and silanes. Iron oxides are environmental friendly, low-cost, and have much higher thermal stability than organic coloring species , iron oxide yellow , IOO iron oxide orange , iron oxide brown  and iron oxide black  were supplied by Deqing Huayuan Pigment Co. Ltd., Zhejiang, China. TEOS (99.9%) and PFDTES (97%) were bought from Gelest. Glass slides (24 mm × 50 mm) were purchased from Menzel, Braunschweig, Germany. H2SO4, anhydrous ethanol, ammonia, diiodomethane, n-dodecane, n-decane, n-hexadecane and toluene were purchased from China National Medicines Co., Ltd. All the reagents are analytical grade.PAL was obtained from Mingguang, Anhui, China. Iron oxide red  was crushed and dispersed in 200 mL of deionized water by mechanical stirring for 20 min. The PAL suspension was left to stand at room conditions for 24 h, during which quartz and other impurities in PAL settled down. Then, the PAL suspension was collected and centrifugated at 6000 rpm for 20 min. Subsequently, the purified PAL was dried in an oven at 105°C to a constant weight, and crushed for 15 s in a shredding machine. The purified PAL was filtered by passing through a 200-mesh sieve.CPAL/IOR), grinding time (tgrinding), concentration of PFDTES (CPFDTES), and concentration of TEOS (CTEOS) were prepared.The PAL/IOR@fluoroPOS suspensions were prepared according to the following procedure. Typically, the mixture of PAL (1.0 g) and IOR (0.05 g) was ground manually in an agate mortar for a period of time  to form the PAL/IOR composite. Then, 0.5 g of the PAL/IOR composite was charged into 43 mL of anhydrous ethanol in a 100 mL conical flask. The mixture was homogenized by sonication for 50 min, and then 7 mL of ammonia solution, 50 μL of TEOS and 0.6 mL of PFDTES were added under magnetic stirring. After reacting at room conditions for 8 h, the PAL/IOR@fluoroPOS suspension was formed. The suspensions with different concentration of PAL/IOR  with 0.2 MPa N−1 using KBr pellets. The XPS spectra were obtained using a VG Escalab 250 Xi spectrometer equipped with a monochromated Al Kα X-ray radiation source and a hemispherical electron analyzer. The XPS spectra were recorded in the constant pass energy mode with a value of 100 eV, and all binding energies were calibrated using the C 1s peak at 284.6 eV as the reference. The TGA analysis was carried out using a STA 6000 simultaneous thermal analyzer  in the range of 25–1,000°C at a rate of 10°C min−1 in N2 atmosphere. CAs and SAs of liquids were measured using a Contact Angle System OCA20  equipped with a tilting table at room temperature. A minimum of six readings were recorded for each sample, and the average values with standard errors were reported.The microstructures of the samples were observed by a field-emission scanning electron microscope . For SEM observation, the samples were fixed on copper stubs and coated with a layer of gold (~7 nm). The FTIR spectra of samples were recorded using a Thermo Nicolet Nexus spectropho-tometer  in the range of 4,000–400 cmFigure The surface of the PAL/IOR coating is flat and the microscale roughness is low Figure . PAL/IOR2, and CF3 groups. The peak corresponding to the C-O group was not detected, indicating absent of the Si-OC2H5 groups and complete hydrolysis of silanes. The chemical composition of the PAL/IOR@fluoroPOS coating was also analyzed by FTIR spectroscopy with PAL/IOR for comparison  and silsesquioxane  were detected . This is attributed to the decreased surface roughness . A too high CPFDTES generated excess fluoroPOS, which buried most of the PAL/IOR nanorods and resulted in evident decrease of the surface roughness  salts instead of solid-state grinding of PAL and IOR. Fe2O3 nanoparticles were formed on the PAL nanorods in the hydrothermal reaction (Tian et al., n−decane is 154° and the SAn−decane is 10° on the coating, which means higher superamphiphobicity than the coating prepared by solid-state grinding. This is because hydrothermal reaction has no influence on the length of the PAL nanorods and the nanorods are kept very well (Figure 2O3 nanoparticles are smaller and are uniformly anchored on the PAL nanorods. Thus, the nanoscale roughness of the coating is higher (Figures Moreover, the PAL/IOR composite can also be prepared by l Figure . In addi Figures , which i2O4, yellow BiVO4 and white ZnO can be anchored on the PAL nanorods via specific reactions (Zhang et al., In fact, nanoparticles of metal oxides in different colors, such as blue CoAln−decane of 95° and a CAn−hexadecane of 148° (Schlaich et al., 2.Compared with the reported superamphiphobic coatings, our coatings showed higher superamphiphobicity and are among the coatings with the highest superamphiphobicity (Chu and Seeger, −1. In comparison with the existing colorful super anti-wetting coatings, the coatings also feature high mechanical, chemical and thermal stability up to 400°C. Moreover, superamphiphobic coatings in different colors can be prepared via the same procedure, and are applicable onto various substrates. We believe that the findings here will shed light on the design of novel colorful super anti-wetting coatings. The colorful superamphiphobic coatings may find applications in many fields, such as anti-climbing of oils and restoration of cultural relics.In summary, a general method has been developed for the preparation of mechanically robust and thermally stable colorful superamphiphobic coatings. The superamphiphobicity is closely related to the surface microstructure and chemical composition of the coatings, which can be regulated by the concentrations of PAL/IOR, PFDTES, and TEOS and the solid-state grinding time. The colorful superamphiphobic coatings feature high contact angles and low sliding angles for water and various organic liquids with surface tension as low as 23.8 mN mNT performed the experimental design and data analysis, and wrote the manuscript; PZ performed experiments and contributed to the data analysis; JZ performed the experimental design and data analysis, and contributed to writing the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The role of gut microbiota in the development of metabolic illnesses has been abundantly demonstrated. Recent studies suggest that gut microbiota alterations may also be related to the development of hypercholesterolemia. Therefore, we aimed to assess differences in the gut bacterial community profiles between hypercholesterolemic subjects and controls. Thirty cases diagnosed with hypercholesterolemia and 27 normocholesterolemic controls were included. A fasting whole blood sample was obtained to determine the lipid profile. In parallel, stool samples were collected and total DNA was isolated to assess the bacterial community profiles by denaturing gradient gel electrophoresis (DGGE). In addition, the Richness, Shannon-Weaver, and Simpson indexes were used to evaluate the richness and diversity of bacterial communities. As expected, serum concentrations of total cholesterol, triglycerides, and LDL-cholesterol were significantly higher in the cases compared with controls. Moreover, DGGE analysis showed a lower richness and diversity of bacterial communities in hypercholesterolemic subjects. In conclusion, our results showed differences in the profiles of bacterial communities between hypercholesterolemic subjects and controls, suggesting a possible role of the gut microbiota in the development of hypercholesterolemia. Cardiovascular diseases (CVD) are the leading cause of death in the world, causing annually about 16 million deaths and more than 21,000 in Chile . Among CDuring the last years, gut microbiota has been related to both the maintenance of health and the development of several diseases . The rolNowadays, precision medicine has sought to improve the understanding of the health-disease process, where a broader description of factors involved in the development of a particular pathology becomes highly relevant. The prior statement led to suggesting that gut microbiota characterization represents a useful aspect into a better comprehension of the cardiovascular health status of an individual . ConsideWe design a case-control study including 30 hypercholesterolemic subjects (cases) diagnosed according to the NCEP criteria  and 27 nBiochemical measurements were performed on serum samples obtained from total blood using standard venipuncture techniques following a 12-h overnight fast. Glucose, triglycerides (TG), total cholesterol (TC), and high-density lipoprotein cholesterol (HDL-C) were quantified using enzymatic-colorimetric methods. Low-density lipoprotein cholesterol (LDL-C) was calculated using Friedewald's formula when TG did not exceed 4.52 mmol/L. Quality of the determinations was controlled by using normal and pathological commercial serums .Stool samples were collected to analyze bacterial community profiles of the gut microbiota by gel electrophoresis with denaturing gradient (DGGE) technique. For the DGGE, DNA was isolated from deposition samples using the Fast DNA Spin  commercial kit, following the manufacturer's instructions. DNA was later quantified by UV spectrophotometry with Infinite® 200 PRO Nanoquant microplate reader . Then, 100 ng DNA was used to amplify a 454 bp fragment of the 16S rRNA gene by touchdown PCR using the EUBf933-GC and EUBr1387 primers .μL of final volume containing MgCl2 (3 mM), GoTaq® Flexi Buffer (1x), dNTPs (0.2 mM each), GoTaq FlexiDNA polymerase (1.25 units), and primers (200 nM each). Touchdown PCR was performed on a MultiGene™ thermocycler  using the following cycling conditions: denaturation at 94°C for 1 minute, followed by a hybridization step using a 0.5°C decrease for each cycle between 65 and 55°C, with 10 additional cycles at 55°C, and the extension step at 72°C for 3 minutes. A final extension of 7 minutes was included. PCR products were visualized by electrophoresis on a 2% agarose gel using a 100 bp DNA marker stained with GelRed™ .PCR was performed in 50 Subsequently, PCR products were loaded onto a DGGE gel (acrylamide/bisacrylamide in 37.5 : 1 ratio) at 8% (w/v) in 1x TAE buffer (20 mM acetic acid and 1 mM EDTA pH 8.0). A gradient of 40 to 60% of denaturing agents (urea 7 M and 40% formamide) was used in DGGE gel preparation. Electrophoretic separation was performed at 20 V for the initial 10 minutes and then at 80 V for 17 hours at constant 60°C. Finally, DGGE gels were stained using SYBR® Gold (Invitrogen™) and the images were acquired using a Geldoc-It® TS2 310 photodocumentation system . Banding patterns were analyzed in the CLIQs 1D Pro software . A nonmetric multidimensional scaling (nMDS) data matrix incorporating the Bray-Curtis similarity index was obtained from the Primer6 software . In addition, we analyzed the pattern of bands to evaluate richness and diversity by the Shannon-Weaver and Simpson indexes. t-test. Statistical significance was set at p < 0.05.Statistical analysis was performed using the IBM SPSS Statics software for Mac, version 23.0 . Data are presented as averages ± standard deviation (SD). Differences between means of continuous variables were evaluated by Student's2) than controls (23 Kg/m2).Anthropometric and biochemical variables of the subjects are summarized in With respect to the molecular analysis performed by DGGE, we observed that the banding profiles differ between cases and controls, which in general were grouped in the two main branches in the dendrogram .Then, this difference was also confirmed by plotting the nMDS analysis, which shows that cases are similar to each other, forming a well-defined grouping .Finally, we found significant differences for the Richness, Shannon-Weaver, and Simpson indexes of the banding profiles between both groups, with a noticeable decrease of the three indexes used in cases with respect to the controls .A very well established association exists between hypercholesterolemia and CVD risk. However, up until now, the wide spectrum of CVD determinants is yet far to be fully understood. Very recently, a clear association between variations in gut microbiota and disease development has been demonstrated, showing a growing interest in the relationship between gut microbes and lipid profile. In the present study, we explored possible differences between bacterial community profiles of the gut tract of hypercholesterolemic individuals and controls. By calculating diversity indexes obtained from the analysis of bacterial DNA from the gut, we have consistently demonstrated that hypercholesterolemic subjects have significantly lower bacterial diversity compared to control individuals. In addition, the nMDS scaling analysis demonstrated the existence of differences among cases and controls, allowing the grouping by similarity of 26 from the 29 hypercholesterolemic individuals.Data obtained are concordant with a 2015 cross-sectional study relating microbiota with BMI, TG, and HDL-C, revealing that healthy lipid levels were associated with an increase in microbial diversity . MoreoveAn interesting result of our study is that hypercholesterolemic individuals presented lower richness and lower diversity compared with control individuals. It has been suggested that attenuation in phylotypes number and alterations in bacterial relative abundance as showed by the studied hypercholesterolemic subjects could modulate cholesterol absorption or modulate cholesterol metabolism at the systemic level. In line with this observation, it has been demonstrated that facultative and anaerobic bacteria located in the large bowel produce secondary bile acids from bile salts secreted by the individual, which can modulate lipid metabolism at both hepatic and systemic levels . On the The approach used in the present study does not permit to identify the specific communities that differ between the groups. However, since it has been suggested that differences in microbial diversity could directly affect hepatic metabolism by exerting an influence on hepatic lipid biosynthesis  as well  Lactobacillus acidophilus or Enterococcus faecium, in subjects having a normal lipid profile and subjects with medium to moderate hypercholesterolemia [ Lactobacillus reuteri was described as an effect associated with increased intraluminal bile acid deconjugation, resulting in reduced absorption of sterols different than cholesterol [Although the microbiota in hypercholesterolemic individuals has not been characterized, a possible role of bacteria as lipid profile modulators in humans has been reported in individuals whose diet was supplemented with probiotics, which are defined as live microorganisms administered in suitable amounts to confer health benefits on the host. Two randomized, double-blind, placebo-controlled studies showed a 4.4% TC and 6.2% LDL-C reduction caused by dairy products enriched witherolemia , 31. In lesterol .Among the limitations of our study, we need to mention that DGGE allows describing qualitatively the bacterial populations present in a particular sample. However, as aforementioned, our approach does not permit to identify which microorganisms could be differentially contained in the group of hypercholesterolemic subjects. Despite this, from a more general perspective, the nMDS ordination plot of the DGGE data showed a clear grouping of the microbiota from hypercholesterolemic individuals, which is not so evident in the control group, with the exception of some of these individuals that appear overlapping with the control group, suggesting that there is a group of predominant phylotypes influencing hypercholesterolemia.Finally, the technical limitations could be corrected in future studies by analyzing microorganisms by means of next-generation sequencing (NGS) methodologies, allowing a much deeper description of the bacterial populations associated with the development of hypercholesterolemia.Our results showed differences in the profiles and diversity of bacterial communities between hypercholesterolemic subjects and controls, suggesting a possible role of the gut microbiota in the development of hypercholesterolemia.


During the breeding period, posterior mean wolf density was 2.55 wolves/100 km2 (95%BCI = 1.87–3.51), and the posterior mean population size was 111.6 ± 18.8 wolves (95%BCI = 81.8–153.6). From simulation studies, addressing different scenarios of non-independence and spatial aggregation of individuals, we only found a slight underestimation in population size estimates, supporting the reliability of SCR for social species. The strategy used here (DNA monitoring combined with SCR) may be a cost-effective way to generate reliable population estimates for large carnivores at regional scales, especially for endangered species or populations under game management.Decision-makers in wildlife policy require reliable population size estimates to justify interventions, to build acceptance and support in their decisions and, ultimately, to build trust in managing authorities. Traditional capture-recapture approaches present two main shortcomings, namely, the uncertainty in defining the effective sampling area, and the spatially-induced heterogeneity in encounter probabilities. These limitations are overcome using spatially explicit capture-recapture approaches (SCR). Using wolves as case study, and non-invasive DNA monitoring (faeces), we implemented a SCR with a Poisson observation model in a single survey to estimate wolf density and population size, and identify the locations of individual activity centres, in NW Iberia over 4,378 km Decision-makers in wildlife policy require reliable population size and density estimates to adopt and justify interventions. Reliability is essential to build acceptance and support in management decisions and, ultimately, trust in managing authorities. Otherwise, speculation and distrust can emerge after decisions are made, and may undermine entire management or conservation strategies3. Incorrect population estimates may lead to misinterpretations of the status of populations, the impact of interventions , or the degree to which conservation goals have been achieved.Estimating the abundance of species is one of the most contentious issues in conservation and applied ecologyPanthera tigris), lions (Panthera leo) or wolves (Canis lupus)8. Clear population targets are often established by managing authorities, and have become political issues, with reliable assessments of changes in large carnivore ranges and population size required to justify actions9.The management of large carnivores is controversial due to the multiple political, socio-economic and conservation interests involved. Information on population size or the impact of interventions is in constant demand, not only by managers, researchers and conservationists, but also by other interest groups. This is exemplified by recurrent debates around large carnivore numbers, particularly centred on endangered and charismatic species, such as in the case of tigers , and whose population targets are often established, compared to other wildlife. Wolf estimates are required to meet legal obligations in both Europe18, and may make wolf population size estimates more homogeneous in a transboundary and regional context. Notwithstanding, many wolf management strategies still combine the number of packs/reproductions with the number of individuals. In Europe, for example, estimates reporting the number of individuals still prevail19, requiring a conversion exercise from the number of packs/reproductions . However, this conversion remains a challenge20 and, in most cases, the data required to calculate conversion factors properly is not available. While the number of packs or reproductions are a reasonable target for wolf monitoring at regional scales17, apart from mismatches between management goals  and monitoring targets , there are cases where estimating the number of wolves may be important. Examples include small and endangered wolf populations, such as the Sierra Morena12 or Mexican21 wolf populations, and populations under game management6.The number of wolf packs or reproductions are often the basis of wolf monitoring26, including non-invasive DNA monitoring27. This method, combined with traditional capture-recapture procedures, is often presented as a promising strategy to achieve robust, feasible and economically affordable population size estimates. Nevertheless, several constraints have been identified when implementing this monitoring strategy. A recurrent limitation is the imprecision when it comes to defining the effective sampling area28. When using traditional capture-recapture procedures, additional spatial information is required in order to define the effective sampling area, such as information from collared individuals30. However, gathering this information may not be budgetary feasible in many cases, particular at regional scales. Moreover, the minimum number and type of collared individuals needed to capture the movement parameters in a population must be representative. On the other hand, encountering probabilities are heterogeneous among those individuals exposed to sampling31.Different field methods and analytical approaches have been used to address the challenge of surveying large carnivore populations at regional scales32, taking into account heterogeneity in encounter probabilities. In SCR approaches, the effective sampling area is estimated based on the underlying spatial point process, using information from individual’s encounters across detectors31. Although it is possible to integrate other sources of spatial information, such as telemetry data33. For large carnivores, within the SCR framework, several field sampling methods have been used to generate spatial encounter data, mainly camera-trapping data36 and non-invasive DNA monitoring39. Occasions  can be accomplished either in space or time . Under this framework, SCR approaches based on a single survey and using a Poisson observation model allows density estimates41.However, the development of spatially explicit capture-recapture approaches (SCR)–linking population size with space by estimating a latent variable representing the location and number of individual’s activity centres–allows the estimation of density, defined as the local intensity of a spatial point processS) –the area that includes all individuals potentially exposed to sampling32. However, both assumptions are violated by multiple species. For example, in social and territorial carnivores, like wolves or lions, a large segment of the population lives in packs or prides, respectively. In solitary carnivores, like many felid species or bears42, adult females and juveniles  stay together for several months within the annual cycle before dispersion. In wolves, the functional unit is the pack, but wolf populations show a varying proportion of non-resident individuals43. Although the size of wolf home ranges is influenced by individual attributes 44, pack cohesion varies throughout the annual cycle46 and pack members may use space differently within pack territories47, spatial overlap of home ranges for pack members being high47.SCR assumes that distributions of animal activity centres are uniformly and independently distributed over the state space  -related with the movement of individuals- obtained from the SCR model, with empirical data from a set of collared wolves in the study area.Here, we combined non-invasive DNA monitoring (faeces) with a SCR Poisson observation model in a single survey to demonstrate the performance of this monitoring strategy in estimating wolf density and population size, and identify the activity centres of wolves at regional scales. Using wolves as illustrative example, we used simulations to show how SCR models perform with species violating the assumptions that distributions of animal activity centres and animal movements are independent18 covering ca. 4,378 km2, and where 11 breeding packs were detected in 201348. During the 2013 wolf breeding period , 317 wolf-like faeces were collected across CM. In collaboration with rangers from the Regional Government of Galicia, faeces were searched along transects distant from human settlements26. Random sampling is not effective to locate wolf faeces; therefore, scat sampling was focused on landscape elements often used by wolves as marking places 26. A minimum of 10 km of transect length was invested per each 10 × 10 km UTM cell, surveying a total of ca. 750 km over the study area  with a SCR Poisson observation model in a single survey in the wolf population of Costa da Morte and surroundings  Figs  and S4, rea Figs  and S2. et al.49 and Appendix S1. MtDNA species identification was achieved for 288 samples (91%). Based on DNA quality, 172 samples were further considered for individual identification using four replicas of 18 Ancestral Informative Markers50. After a Bayesian analysis to exclude dogs , ninety-five wolf samples achieved a consensus genotype (55%) with <20% missing data, following rules defined in Godinho et al.50. Multiple factors can influence the success rate of genotyping and individual identification, such as the age of the wolf scat (related to the presence of odour)51. Nevertheless, the success rate observed in this study was similar to other values reported in studies using non-invasive DNA51. Estimated allelic dropout across loci was ADO = 0.033, and estimated false alleles were FA = 0.00549. After regrouping of identical genotypes49, we identified 65 individual wolves. This dataset had a probability of identity (PID) = 4.19 × 10−8 and a PIDsiblings = 4.01 × 10−4 (Appendix S1).Details on genotyping are provided in Pacheco si representing “where the animal i of the N population size lives”. Formally, the sequence of points s1, …, sN is a realization of a latent spatial point process, and allows the estimation of density using SCR models. SCR assumes that every individual i in the population has its own activity centre si, and that all activity centres are distributed across the study area. Moreover, encounter probability (pij) is a decreasing function of distance between the activity centre of the individual i (si) and the location of the detector j (xj). Therefore, SCR addresses the movement of individuals by assuming that each individual has an activity centre, and that the probability of capture individuals is a function of the distance from the activity centres to detector locations. In our case, because the collection of wolf faeces was not attached to physical traps, our detectors were the centroids of the cells within the sample grid, and the effort invested in searching samples inside cells was used as a “detector level” covariate.We applied a SCR modelling approach to estimate wolf density, population size and the distribution of individual’s activity centres in CM. Conceptually, activity centres are points 2) cell grid layer over the study area. Cell size was well below the average (±SD) home range size for subadult/adult wolves belonging to packs in NW Iberia (122.1 ± 93.6 km2)52. This cell size was selected to avoid an excessive loss of resolution in the scale parameter sigma (σ) –a parameter that determines the decline of detection frequency of individuals in detectors with increasing distance from their activity centres–, resulting in 174 5 × 5 km cells in CM , because we used a single occasion.We built a grid cell layer with the size of cells being small compared to typical wolf home ranges. Considering previous information on the spatial ecology of wolves in NW Iberia, we created a 5 × 5 km  in each terrestrial section of the cells as a covariate accounting for sampling effort α0 and α1 were the parameters to be estimated. The total number of activity centres (N) were calculated using the data augmentation approach32. All-zero encounter histories  were added to encounter histories of detected individuals. We generated the state space (S) adding a 10-km buffer to the detector grid. This distance must be >2.5 × σ32. The resulting S was ca. 7,500 km2. We used an application of the “zero’s trick” to buffer an irregular detector array  without discretizing the state space53. We scaled and centred S dividing the spatial coordinates (m) by 10,00032.As several cells share land and sea surfaces in CM Fig. , we usedM0) in a Bayesian framework using Nimble v.0.6-254 and R55 (Appendix S2). We ran 3 chains of the MCMC sampler with 50,000 iterations each, yielding 150,000 total samples from the joint posterior distributions. To check for chain convergence, we assessed MCMC convergence and mixing by visually inspecting trace plots for each parameter of interest, and we calculated the Gelman-Rubin statistic R-hat56 using the R package coda57, where values below 1.1 indicated convergence. We evaluated the goodness of fit of the model by using the Bayesian p-value approach and two fit statistics 32: i) individual encounter frequencies, which evaluates heterogeneity in encounter frequencies due to space ; and ii) detector frequencies, which is based on aggregating over individuals and replicates to form centroid-encounter frequencies (Appendix S2).We fitted a null Poisson distributed observation model (S. We explored the influence of such violations on population density estimates by carrying out three simulation studies (described in Appendix S3). We tested for the influence of the randomness in the location of wolf packs across the state space, because the identification of the spatial location of activity centres is more accurate inside the detector grid.SCR approaches assume that all individuals are uniformly and independently distributed over the state space σ from M0 with two sigma parameter estimates based on wolf spatial behaviour , chemically immobilised by intramuscular injection of medetomidine  and equipped with GPS-GSM collars . Our dataset was comprised of 9 males and 9 females, of ≥2 years, and considering individuals integrated and non-integrated within packs. We used a total dataset of 5,432 locations . The average monitoring period for collared wolves was 161 days (range 14–397). In order to provide additional support to this modelling approach, we also compared sigma estimates during the same period of the year . We estimated individual home ranges (km2) using the 95% fixed-kernel method with the R package adehabitatHR58.We evaluated the performance of this modelling approach by comparing α = 0.05, A was the average home range area (m2)32.We calculated the scale parameters S and the location of known breeding packs in CM. We used the information on the number and spatial location of wolf breeding packs from the official wolf monitoring survey carried out in CM in 201348 26.We also evaluated the spatial mismatch between the spatially explicit posterior mean density of activity centres for wolves across 43, our assumption was based on 88 field observations of breeding packs at rendezvous sites 59 in N Iberia, where the average number of observed pups was 4.82 (95%CI 4.57–5.08), the average number of subadults was 1.67 (95%CI 1.25–2.08) and the average number of adults was 1.98 (95%CI 1.74–2.22)60. Considering the number of known breeding packs in CM in 2013 (11 packs)48 and the range of individuals per pack in late summer (7–9 wolves), we transformed the number of packs into number of wolves belonging to packs.Finally, we estimated the proportion of wolves that were part of known breeding packs. To do this, we assumed that in late summer, breeding wolf packs oscillated between 7 and 9 individuals, including the year’s pups. Although pack size is variable in wolvesWolves were captured under permits 19/2006, 71/2009, 86/2011, 095/2013 and 8765/2015 from the Regional Government of Galicia. All field procedures were carried out in accordance with animal welfare regulations.M0) showed convergence and R-hat < 1.1. The posterior density estimate 2  = 1.87–3.51; Table 4)  were detected once, nine wolves were detected twice and, respectively, three, one and three individuals were detected 3, 4 and 5 times (the average number of captures by wolf was 1.46). The number of individuals captured per detector is shown in Table From simulation studies, using clusters of individuals and repulsion between clusters (packs in our case) we tested the potential role of spatial aggregation and non-independence of individuals, and we only found a slight underestimation in population size estimates (Appendix S3). The adequacy of the Root-Mean-Squared-Error for the posterior mean for the parameter 2; whereas this figure was 233.1 km2 when we considered only locations within the interval March-October. The estimates for 4). These values were within the 95% BCI of the posterior estimate for sigma from M0  across an area of >4,000 km2. A critical point in SCR models is the need for sufficient spatial recaptures for reliable estimates of σ32. Considering the average number of captures by wolf (1.46), the number of individuals captured across detectors (65), and the space among detectors (5 km), our spatial parameters can be considered reliable32. Count-based observation models, such as the Poisson model, using multiple detections of the same individual at the same detector, and being based on a single survey, allows the estimation of model parameters successfully. For situations in which behavioural or time-related covariates –across the sampling occasions- are not available, the property of additivity of the Poisson distribution allows the aggregation of the observation data, facilitating the use of the Poisson model based on a single survey to estimate model parameters 32. Nevertheless, when implementing encounter frequency models, like a Poisson model, encounter frequencies over short periods are mainly due to individual behaviour. Moreover, it can be questionable to consider that all encounters are independent, which deserves further investigation.We combined non-invasive DNA monitoring (faeces) and a SCR approach, with a Poisson observation model using a single survey, to estimate density, population size and the location of activity centres in wolves at a regional scale. The number of sampling surveys can constrain the application of SCR approaches at regional scales. We used the null model 48. In fact, the spatial location of some aggregations of activity centres corresponded with the location of previously known breeding packs in the study area50. The combination of both wolf surveys , together with information on pack size60, allowed us to approximate the number of wolves not linked to breeding packs in late summer, between 16 and 25% of wolves in our case. This estimate is similar to those obtained during winter wolf monitoring in other study areas across the wolf range. The percent of non-resident wolves in winter monitoring in different North American wolf populations ranged from 7 to 20%43. Interestingly, the above comparisons suggest that when using the number of packs as a target for wolf monitoring, underestimation in population estimates may occur.The location of wolf activity centres fully matched the approximate locations of detected breeding packs in CM. But we also detected non-overlapping aggregations of activity centres Fig. , probablM0; Table 27 may be behind the small differences observed in sigma, which could lead to some small bias in population estimates. Young and lone wolves more often deposit their faeces off-trail compared to adult and territorial individuals63. On the other hand, the persistence of wolf faeces may facilitate the detection of scats and the occurrence of spatial recaptures.For species with large spatial requirements, such as large carnivores, and short study periods, the area of activity centres used during the sampling period may represent only a section of the total animals’ home range. In our case, the sampling period spanned several months during the breeding and pup-rearing periods, and the posterior estimate for sigma 65. Importantly, our results highlight the importance of setting the detector grid appropriately when monitoring species in which individuals are aggregated. Outside the detector grid, the individuals from a cluster , and randomly located, were detected fewer times and with fewer spatial and non-spatial captures (Appendix S3), resulting in less accuracy and precision for The assumptions that all individuals are uniformly and independently distributed over the state space 66 and different populations are under game management. The use of a single survey is expected to be less costly compared to multiple visits to detectors64. Moreover, the use of this monitoring strategy is expected to have positive implications for the adaptive management of these species. Adaptive management is a systematic approach to improve resource management by learning from management outcomes67. Because it is a learning-based process68, monitoring is an essential step in the adaptive management process. In our case, the ability to obtain reliable population estimates – quantifying uncertainty - that are reproducible over time is fundamental to assess the impact of interventions properly, which can be achieved with this monitoring strategy.The combination of non-invasive DNA monitoring  and SCR modelling approaches can be used to monitor species at regional scales accurately, such as large carnivores and large herbivores. Reliable population size estimates are particularly important for these species considering that ca. 60% of the world´s largest carnivores and herbivores are classified as threatened with extinction on the International Union for the Conservation of Nature (IUCN) Red ListUrsus arctos, in Europe)69, which should be properly designed to record all required information, including sampling effort.Apart from funding to carry out genetic analyses, the main challenge in implementing this monitoring strategy is an appropriate sample collection to ensure a sufficient number of recaptures in a single survey. In this regard, an alternative to optimize the use of limited resources, without compromising the collection of samples, may be the integration of multiple trained stakeholders and volunteers in sample collection (see an example for brown bears, Supplementary Information


Diagnosis of a low-grade periprosthetic joint infection (PJI) prior to revision surgery can be challenging, despite paramount importance for further treatment. Arthroscopic biopsy of synovial and periprosthetic tissue with subsequent microbiological and histological examination can be beneficial but its specific diagnostic value has not been clearly defined.20 consecutive patients who underwent percutaneous synovial fluid aspiration as well as arthroscopic biopsy due to suspected PJI of the hip and subsequent one- or two-stage revision surgery at our institution between January 2012 and May 2015 were enrolled. Indication was based on the criteria (1) history of PJI and increased levels of erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP), (2) suspicious cell count and differential but negative bacterial culture in synovial aspirate, (3) early loosening (<less than 2 years), or (4) persisting pain without loosening but history of a PJI. At least two criteria had to be fulfilled in order to perform an arthroscopic biopsy.Best overall diagnostic value was identified for arthroscopic biopsy and a combination of bacteriological and histological analysis with a sensitivity of 87.5%, specificity of 100% and accuracy of 95%. Bacteriological assessment of synovial aspirate revealed a sensitivity of 50.0%, specificity of 91.7%, and accuracy of 75%. ESR and CRP yielded a sensitivity of 75.0% for either hematologic test and specificities of 87.5 and 66.7%, respectively.In conclusion, our data indicate that arthroscopic biopsy is superior to ESR and CRP as well as joint aspiration and their combinations. Concurrent microbiological and histological examination of the biopsy specimens allows for identification of the causative pathogen and its susceptibility pattern in order to preoperatively plan the surgical strategy as well as the antibiotic regimen. Moreover, intraarticular mechanical failure can be detected during hip arthroscopy emphasizing its diagnostic value. Level II diagnostic study. Osteoarthritis (OA) of the hip is a disabling condition with significant and rising incidences due to the demographic development in modern industrial countries. Among different symptomatic treatment options, total hip arthroplasty (THA) remains the only causal therapy. Thus, the number of THA performed in the USA is estimated to triple until 2030 leading to a significant increase of revision surgery .coagulase-negative staphylococci (CNS), often lacking severe inflammatory symptoms. Despite paramount importance for further treatment, diagnosis of a low-grade PJI prior to revision surgery can be challenging.One major reason for revision arthroplasty is periprosthetic joint infection (PJI). Recent literature suggests that revision surgery of THA is performed in up to 15% of the cases due to PJI . In contIn addition to clinical findings, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and percutaneous aspiration of synovial fluid for evaluation of cell count and differential as well as microbiological analysis depict routinely employed diagnostic tools . These tSimilarly, for percutaneous aspiration of synovial fluid sensitivity varies from 12 to 89% and specificity from 50 to 100%  compared the diagnostic yield of ESR and CRP, cell count and differential of synovial aspirate, microbiological culture of aspirate and biopsy samples, histological analysis of biopsy specimens as well as reasonable combinations of these diagnostic tools and (2) hypothesized that arthroscopically controlled tissue biopsy with subsequent microbiological and histological analyses exhibits superior results. To the best of our knowledge, it is the first prospective study concerning the diagnostic value of hip arthroscopy in tentative PJI.All patients who underwent percutaneous synovial fluid aspiration as well as arthroscopic biopsy due to suspected PJI of the hip and subsequent one- or two-stage revision surgery at our institution between January 2012 and May 2015 were enrolled.Indication for arthroscopic biopsy prior to arthroplasty revision surgery was based on the tentative diagnosis of a PJI. According to our own evidence-based diagnostic algorithm, an aspiration without anesthesia was performed in all patients prior to inclusion in our study. In case of obvious infections, for example pus in the aspirate or presence of a fistula, patients were excluded. Only patients with negative or unclear results from an aspiration without anesthesia and the presence of at least 2 of the following 4 criteria were enrolled: (1) history  and increased CRP (greater than 0.5 mg/dl) or ESR (greater than 30 mm/h), (2) conspicuous cell count and differential in synovial aspirate, (3) early loosening (<less than 2 years), or (4) persisting pain without loosening but history of a PJI. Antibiotic treatment, if applicable, was terminated at least 2 weeks prior to the intervention.Percutaneous aspiration and arthroscopic biopsy were performed in the operating room under strictly aseptic conditions and general anesthesia. The patient was placed supine on a radiolucent table. After preoperative skin preparation with antiseptic agent (iodine) and sterile covering, a small skin incision for a standard anterolateral arthroscopy portal was made. Under fluoroscopic control, a 14-gauge spinal needle was placed within the joint and at least 4 ml of synovial fluid was attained. The aspirate was divided for cell count and differential analysis as well as bacterial cultures. For the latter, the aspirate was transferred into anaerobe and aerobe blood culture flasks.Subsequently, an anterolateral and lateral arthroscopy portal were established. Prior to instillation of arthroscopy fluid, 5 specimens from different locations of the periprosthetic space and the synovia were obtained under direct optical control. All biopsy samples were divided for histological analysis and microbiological cultures. After instillation of arthroscopy fluid, a diagnostic exploration for wear disease or mechanical reasons of prosthetic failure completed the arthroscopy.Based on the results of the biopsy, one- or two-stage arthroplasty revision surgery was performed. Intraoperatively, at least 5 samples including synovial fluid, synovial tissue, and periprosthetic membrane were obtained. Again, all samples were divided and subjected to bacteriological and histological analysis. Perioperative antibiotics were withheld until retrieval of all tissue samples. The combined microbiological and histological results of the specimens obtained during revision surgery as well as sonication of the removed implant were used as definitive diagnostic test.All samples for microbiologic analysis were routinely inoculated for 10 days. In case of any suspicion of growth, samples were subcultured in a thioglycollate broth for another 4 days. A result was considered positive if at least two cultures showed growth of the same pathogen. Isolated growth in only one culture was considered as contaminant and thus as negative result except for concurrent positive histologic findings.Specimens for histological workup were routinely processed and stained using periodic acid-Schiff (PAS) and CD15 immunohistochemistry. During further analysis, neutrophilic granulocytes in the histologic sections were enumerated. A threshold of ≥23 neutrophilic granulocytes in 10 high power fields (HPF) was considered as PJI as previously recommended by Morawietz et al. .Final diagnosis in terms of the presence or absence of a PJI was made upon discussion in our “Endoprosthetic Infection Board” together with microbiologists and pathologists specialized in periprosthetic infections.U test for independent samples. A p value ≤0.05 was considered statistically significant. Following Rothman, no Bonferoni adjustment for multiple testing was performed due to the observational nature of our data [All diagnostic parameters, ESR, CRP, cell count and differential of synovial aspirate, microbiologic culture of aspirate and biopsy samples, histologic results of biopsy specimens as well as any reasonable combination were compared to the definitive results obtained during arthroplasty revision surgery. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy , positive and negative likelihood ratios  as well as 95% confidence intervals were calculated. ESR, CRP, and cell count values were compared using SPSS Software  and the Mann–Whitney-our data .Best overall diagnostic value of all procedures investigated in this study for identification of PJI was achieved by arthroscopic biopsy and a combination of bacteriological and histological analysis of the specimens Table . Adjacenp = 0.008). Similar to ESR, in patients with present PJI, a significantly higher CRP-value of 1.91 ± 1.54 mg/dl compared to non-infected hip joints  was observed. However, 25% of hips with PJI showed normal CRP values of 0.5 mg/dl or less. Similar results were obtained for percutaneous aspiration of synovial fluid and subsequent analysis of cell count and differential as shown in Table p = 0.032). Likewise, bacteriological assessment of synovial aspirate or arthroscopic biopsy specimens revealed similar diagnostic accuracies , whereupon Staphylococcus epidermidis was found in 62.5%. Inoculation time until a culture was found positive varied depending on the bacterial strain and is shown in Table In total, 8 out of 20 cases were classified as PJI according to revision surgery resulting in a prevalence of 40%. Overall, 4 different microorganisms were identified (Diagnosis of low-grade PJI frequently caused by low-virulent bacterial strains of the skin flora prior to revision surgery can be challenging. However, the accuracy of preoperative diagnosis is of fundamental importance because treatment strategies differ greatly between septic and aseptic revision surgery with expansive consequences for the patient .Among routinely applied diagnostic tools, ESR and CRP are widely available, non-invasive and cost effective. In our study, we found a sensitivity of 75% and specificity of 87.5% for ESR as well as a sensitivity of 75% and specificity of 66.7% for CRP. Although sensitivities of over 90% have been published for ESR and CRP, in a recent metaanalysis Berbari et al. report pooled sensitivities of 75 and 80% as well as specificities of 70 and 74%, respectively, confirming our results . HoweverMany authors propose routine joint aspiration prior to any arthroplasty revision surgery even in the absence of increased ESR and CRP levels or history of PJI , 17, 25.Greatest diagnostic value in our study was observed for concurrent microbiological and histological examination of arthroscopically obtained biopsy specimens calculating to a sensitivity of 87.5% and specificity of 100%. In contrast to our results, Cross et al. report an inferior sensitivity of 41% of synovial biopsy utilizing a fine-needle biopsy technique and local anesthesia compared to sole percutaneous joint aspiration for diagnosing PJI in a retrospective study of 110 THAs . LikewisMoreover, during hip arthroscopy, we could identify intraarticular mechanical failure including wear disease and anterior impingement in 20% of our cases representing diagnostic challenges as previously suggested by Pattyn et al. . These rIn conclusion, our data indicate that arthroscopic biopsy is superior to ESR and CRP as well as joint aspiration and their combinations. Concurrent microbiologic and histologic examination of the biopsy specimens allow for identification of the causative pathogen and its sensitivity pattern in order to preoperatively plan the surgical strategy as well as the antibiotic regimen. Moreover, intraarticular mechanical failure can be detected during hip arthroscopy emphasizing its diagnostic value. Indication for arthroscopic biopsy, however, should be carefully considered and based on history of PJI, clinical findings, radiographs, increased levels of ESR and CRP, and conspicuous joint aspirate.


There is a high hospitalization rate for diabetic patients. Since retinopathy and albuminuria are both important manifestations of microvascular disease in diabetes, our aim was to investigate the effect of retinopathy and albuminuria on long-term mortality in type 2 diabetic inpatients through this observational cohort study.Type 2 diabetic inpatients given a primary diagnosis of poor glucose control were consecutively enrolled during their hospitalization periods. Clinical information was collected through review of each patient’s medical records, and mortality data were obtained from the national registry in Taiwan.A total of 761 type 2 diabetic inpatients were enrolled in the study with a median follow-up period of 6.6 years . Patients in the Albuminuria(−)/Retinopathy(+), Albuminuria(+)/Retinopathy(−) and Albuminuria(+)/Retinopathy(+) groups had significantly higher risks of all-cause mortality and cardiovascular mortality than those in the Albuminuria(−)/Retinopathy(−) group. However, among patients with albuminuria, there was no significant difference in cumulative mortality between those with and without retinopathy (P = 0.821). A decrease in the estimated glomerular filtration rate (eGFR), but not retinopathy, was an independent predictor of all-cause mortality  and cardiovascular mortality  in type 2 diabetic inpatients with albuminuria.Albuminuria in type 2 diabetic inpatients is a strong predictor of long-term mortality after discharge from the hospital. Retinopathy is an independent predictor of mortality in type 2 diabetic inpatients without albuminuria but not in those with albuminuria. A low eGFR is a better predictor of mortality than retinopathy in type 2 diabetic inpatients with albuminuria. Diabetes mellitus is a complex metabolic disorder, and poor blood glucose control is associated with sequential chronic microvascular complications . AlbuminIn addition to nephropathy, retinopathy is another significant manifestation of microvascular disease in subjects with diabetes . A high Since there is a high hospitalization rate in subjects with diabetes , screeniThis study was conducted in the Endocrinology and Metabolism ward of Taichung Veterans General Hospital. Data collection was performed through the review of medical records of the diabetic patients hospitalized between August 1, 1996 and August 31, 2007. In general, all hospitalized type 2 diabetic patients, along with type 1 patients with a diabetic duration of more than 5 years, underwent urine collection and ophthalmology consultation for the evaluation of microvascular complications before being discharged. Patients were included in the study if (1) they were admitted due to a primary diagnosis of poor glucose control, (2) they had undergone ophthalmology consultation, and (3) urinary albumin excretion and serum creatinine had been assessed. Patients were excluded from analyses if (1) there were any inconsistent interpretations of eye assessments during hospitalization, (2) they had been hospitalized in critical condition, with a systolic blood pressure lower than 80 mmHg, or (3) they had died in the hospital. In the case of patients who had been hospitalized more than once during the study period, only the records of their last admission were analyzed.Mortality data up to December 31, 2011 were obtained from the Collaboration Center of Health Information Application, Department of Health, Executive Yuan, Taiwan. This study complied with the tenets of the Declaration of Helsinki, and the research protocol was approved by the Institutional Review Board of Taichung Veterans General Hospital.Based on the standard procedure in our ward during this period, all fundoscopic data were reviewed by ophthalmologists. If any abnormal findings were discovered by their fundoscopic assessments, retinal angiography  was performed to confirm a retinopathy diagnosis. Patients were excluded from the analysis if the interpretations were inconsistent between fundoscopy and angiography. In the present study, we defined the presence of diabetic retinopathy including non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR) .−1.154 × [age (year)]−0.203  mL/min/1.73 m2 based on the modification of diet in renal disease (MDRD) study equation Continuous data were presented as the mean ± standard deviation (SD). One-way analysis of variance (ANOVA) was used to compare the differences among groups. Pairwise multiple comparisons were performed to determine the significance of differences between two groups after ANOVA had revealed any statistical significance. Chi square test was used to compare categorical variables across the groups. The overall significance of univariate survival analysis was detected through the use of the log-rank test using Kaplan–Meier analysis. Multivariate Cox proportional hazards regression analyses were conducted to determine the hazard ratios. The statistical significance was set at P < 0.05. Statistical analysis was performed using SPSS 22.0 .A total of 855 admissions satisfied the inclusion criteria; however, 76 admissions were excluded, including 24 admissions with inconsistent retinopathy interpretation between fundoscopy and angiography, 4 admissions in which the patients died or underwent shock, and 48 admissions after which patients were repeatedly hospitalized during the study period. Furthermore, 17 patients were excluded due to having type 1 diabetes and one patient with diabetes due to chronic pancreatitis was also excluded in the enrollment. Therefore, a total of 761 diabetic inpatients were enrolled for analyses. Based on ACR, there were 207 (27.2%) patients with albuminuria and 554 (72.8%) without albuminuria. Based on fundoscopic examination, there were 330 (43.4%) patients with retinopathy and 431 (56.6%) without retinopathy among all study subjects. The prevalence of retinopathy was higher in patients with albuminuria than in those without . Over a median period of 6.6 years  after discharge from hospital, there were 409 (53.7%) subjects who died during the follow-up period. Among the patients without albuminuria, the cumulative mortality rate of patients with retinopathy was significantly higher than that of patients without retinopathy . However, among patients with albuminuria, the cumulative mortality rate was not significantly different between those with retinopathy and those without  /Retinopathy(−)], patients with retinopathy but no albuminuria [Albuminuria(−)/Retinopathy(+)], patients with albuminuria but no retinopathy [Albuminuria(+)/Retinopathy(−)], and patients with albuminuria and retinopathy [Albuminuria(+)/Retinopathy(+)]. Table During the follow-up period, Cox regression analysis showed that patients in the Albuminuria(−)/Retinopathy(−) group had the lowest risk for all-cause mortality and cardiovascular mortality. Patients in the Albuminuria(−)/Retinopathy(+) group had significantly higher all-cause mortality  and cardiovascular mortality  than patients in the Albuminuria(−)/Retinopathy(−) group. Patients in the Albuminuria(+)/Retinopathy(−) group had significantly higher all-cause mortality  and cardiovascular mortality , and patients in the Albuminuria(+)/Retinopathy(+) group also had significantly higher all-cause mortality  and cardiovascular mortality  than patients in the Albuminuria(−)/Retinopathy(−) group. These conclusions were made after data were adjusted for age, gender, body mass index, systolic blood pressure, current smoker, diabetes duration, HbA1c, chronic kidney disease, total cholesterol, triglycerides, insulin treatment, and angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker treatment (Table In the patients with albuminuria, Table Diabetic retinopathy is associated with systemic vascular inflammation , 14, andPrevious research has shown that albuminuria is a predictor of mortality in Asian as well as Caucasian diabetic patients , 22. RecThere is a high prevalence of retinopathy among diabetic patients with albuminuria . TherefoThe mortality rate of the diabetic population is 1.63-fold higher in comparison to the general population based on the data from the National Register of Deaths . FurtherScreening for retinopathy and nephropathy in diabetic patients is mostly done in the outpatient department. In view of the high mortality rate in diabetic inpatients admitted for poor glucose control, it is essential to routinely assess these predictors of mortality during hospitalization. However, evidence of the value of screening for retinopathy and albuminuria in hospitalized diabetic patients has not previously been adequately presented. Although various causes may bring about hyperglycemia in hospitalized type 2 diabetic patients, our findings suggest that routine screening for retinopathy and urine albumin excretion can be helpful in predicting mortality after discharge. Furthermore, as noted in a previous report, approximately 38% of hospitalized patients have diabetes, and more than 30% of those are newly diagnosed cases . TherefoThere were some limitations in the present study. First, there were daily variations in urinary albumin excretion, so one should not rely on a single measurement . HoweverThe presence of albuminuria is an important predictor of long-term mortality in type 2 diabetic inpatients admitted due to poor blood glucose control. In type 2 diabetic inpatients without albuminuria, the presence of retinopathy is significantly associated with a higher long-term mortality. In type 2 diabetic inpatients with albuminuria, a low eGFR, but not the presence of retinopathy, is significantly associated with higher long-term mortality. In view of the increased risk of mortality after discharge, it is important to screen all hospitalized type 2 diabetic patients for nephropathy and retinopathy.