Fluorographene, formally a two-dimensional stoichiometric graphene derivative, attracted remarkable attention of the scientific community due to its extraordinary physical and chemical properties. We overview the strategies for the preparation of fluorinated graphene derivatives, based on top-down and bottom-up approaches. The physical and chemical properties of fluorographene, which is considered as one of the thinnest insulators with a wide electronic band gap, are presented. Special attention is paid to the rapidly developing chemistry of fluorographene, which was advanced in the last few years. The unusually high reactivity of fluorographene, which can be chemically considered perfluorinated hydrocarbon, enables facile and scalable access to a wide portfolio of graphene derivatives, such as graphene acid, cyanographene and allyl-graphene. Finally, we summarize the so far reported applications of fluorographene and fluorinated graphenes, spanning from sensing and bioimaging to separation, electronics and energy technologies. At the same time, Cheng et al. N-methyl-2-pyrrolidone (NMP) N,N-dimethylformamide (DMF) 2O2) with chlorosulfonic acid (HSO3Cl) Exfoliation of multilayer materials is a well-established approach, which is successfully applied, e.g., for production of graphene nanosheets. In the liquid-phase exfoliation process, a solvent is used as an intercalating agent, weakening the van der Walls interactions 2 and XeF2 to 24% and 100% degree of fluorination Mechanical exfoliation A represeca. 600 °C, as SEM analysis revealed.Finally, another reported method for delamination and expansion of GrF is thermal exfoliation. A partially fluorinated graphite was thermally exfoliated by inserting the solid sample in a preheated furnace at 800 °C, and further used for film formation and electrochemical testing 2.2sp2-hybridized carbons of graphene lattice, forming C-F sp3 bonds and producing fluorinated graphenes. For the direct gas-fluorination of graphene, one of the most common fluorinating agents is xenon difluoride (XeF2) gas and it was utilized for the fluorination of graphene at various temperatures under an inert atmosphere 2, providing a stoichiometric material C1.0F1.0 fully fluorinated on both sides, due to the effective etching on the Si substrate by reactive gas 2) gas, another important fluorination agent, was applied to fluorinate graphene and graphene derivatives at various temperatures and pressures 2Fluorination strategies are based on the model by which graphene  is placed into a reactor with fluorination agents, which are used as precursors for the generation of active intermediates with the aid of either thermal, pressure, or irradiation initiation B. These 4622/Si substrate and then, it decomposed under laser irradiation, generating active fluorine radicals, which reacted with carbon lattice and formed C-F bonds, providing fluorinated graphene C4F 3 in liquid Br2Plasma fluorination is an alternative way for fluorination of graphene, targeting to the synthesis of controllable fluorinated graphene materials. According to this technique, generated fluorine radicals adsorb onto carbon lattice and create different C-F bonds. The fluorine-based compounds CF26, SF4, and MoF62 and to improve the controllability of the C-F bonding character. At that point, it is worth mentioning that the approach above has been also used for the preparation of fluorographane through treatment of graphane with F23-etherate 6) All the methods discussed above employ graphene or bulk GrF for the preparation of fluorinated graphene or fluorographene. However, in the last years, there has been an increasing number of publications regarding the fluorination of GO, synthesizing fluorinated graphene oxide (FGO). Direct gas-fluorination has been successfully applied to the fluorination of GO, using as precursors F3sp2/sp3) ratio significantly affect the electronic and optical properties of fluorinated graphenes. Already a small amount of fluorine atoms in the structure give rise to a band gap opening 1F1 ratio, whereby other geometrical configurations differ only slightly from values calculated for the chair conformation The incorporation of fluorine atoms onto carbon lattice and the C/F (C 0W0@PBE level for FG showed an excitonic peak at 5.14 eV In order to study photoluminescence (PL) of FG, material dispersion in acetone was excited by 290 nm at room temperature −1 and 1345 cm−1. According to Fourier transform infrared (FTIR) spectroscopy, FG exhibits a strong band at 1260 cm−1, which is attributed to the covalent C—F bond stretching −1 and 1084 cm−1, corresponding to the stretching vibration of the C—F covalent bonds and the semi-ionic stretching vibration of C—F bonds, respectively −1, ascribable to the semi-ionic C-F bond, progressively transforms to covalent C—F bond, which is exhibited as a strong band at 1211 cm−1−1, due to the local wagging motion of the C-F bond. In the case of fluorine dimer, IR signal appeared at 1150 cm−1, originated by the local stretching motion of the bond formed by the C—C atoms connected to the fluorines.Another significant proof for the optical transparency of FG is the absence of Raman signals. That happens because the energies of the lasers, which are used for Raman spectroscopy, are lower than the band gap 2 (12%) and C-F3 (2%) species were also present, owing to defects at free edges 2 (∼289.9 eV), C—F2 (∼292.1 eV), and C—F3 (∼293.7 eV) −1, while in the fully fluorinated structure it amounts to 112.3 kcal mol−119F magic angle spinning (MAS) NMR studies on fluorinated graphite showed that the strength of the C—F bond, or its ionic/covalent character, could be also probed with NMR, according to which lower chemical shifts point to higher covalent character X-ray photoelectron spectroscopy (XPS) is a powerful technique providing information about elemental composition and binding conditions of elements in FG. According to XPS data, C—F type was the major bond (86%) in this material, while smaller fractions of C-F1F1 was found to be 2.48 Å, slightly larger than for graphene (2.46 Å). The value of the lattice parameter is in good agreement with the theoretical calculations (α = 2.48 Å), and it corresponds to the chair conformation with AA stacking sequence, the most stable structure sp3 C—C bonds, which are larger than the sp2-type bonding of graphene. The C—C and C—F bond lengths and the repeating unit of FG are shown in −2−2) than graphite Scanning and transmission electron microscopy (SEM and TEM) provide significant information about the layered morphology of FG see B, while In order to utilize FG for bioapplications, it was necessary to examine its biocompatibility and potential toxicity in cells. For that reason, extensive studies were carried out 4®), such as chemical stability in many solvents and high hydrophobicity xFy products evolve from the material Regarding the chemical behavior of FG, it was considered as an inert material, presenting similar properties to GrF and polytetrafluoroethylene  + KF + 1/2 I2. Additionally, graphene was produced by reduction of FG, utilizing either triethylsilane or zinc nanoparticles 2F(semi-ionic) + CH3C(O)CH3(l) → HF + 2C(s) + C2F + CH3C(O)CH3(l)As already mentioned, defluorination of FG is an important approach for its transformation to graphene. For that aim, a significant number of methods have been developed. They are mainly classified into two groups: (a) chemical and (b) thermal reduction. Robinson et al. Regarding the nucleophilic substitution of FG and the preparation of covalent functionalized graphene derivatives, N-, O-, S- and C-nucleophiles have been applied for that purpose see . Ethylensp2 carbons of the graphene lattice, according to [1 + 2] cycloaddition reaction On the other hand, the modification through the formation of C—C bonds between carbons of FG and carbons of the organic units had not received the proper attention and only the last years some remarkable works were reported. In the first work, chlorocarbene, generated in situ by chloroform after treatment with NaOH, attacked electrophilic carbons of FG, detaching fluorine atoms from FG and forming chloro-terminated cyclopropanic rings with the newly formed 52. At that time, there were no reports on the use of single sheets of FG. Nevertheless, the layered nature, low surface energy, and facile exfoliation of GrF plays a significant role in lubrication −1−1GrF and organosiloxane derivatized GrF were studied as solid lubricants and lubricant additives since ’60 s and ’70 s In the case of batteries as well, intercalation and even reactions  FG has also potential in electrocatalytic applications. Theoretical studies suggest that partially fluorinated graphene can act effectively as an efficient metal-free catalyst for oxygen reduction reaction (ORR) −1. This was achieved through preparation of hydroxyl-substituted fluorographene sp2-based magnetism in 2D systems and particularly room temperature sustainable magnetic ordering, pave the way for the future organic spintronic applications.Theoretically it has been indeed predicted that spin density can emerge in FG and be modulated by changing the degree of F coverage 2 and its separation from N2 have been predicted by molecular dynamic simulations upon fluorination of a pore rim in graphene 2O, SO2, H2S, and CO2) over N2, O2, and CH4. Therefore, applications are envisioned on separation of CO2 and SO2 from flue gases, purification of natural gas, and removal of H2O from air. A significant advantage is predicted for porous FG, related to the fact that gas molecule separation is not dependent on size-exclusion mechanism, but on interaction strengths. Therefore, there is no need for contiguous and unbroken films, but only large accessible surface area is required. In the same area of environmental and separation applications, fluorination of edge carbon atoms of a pore in a graphene sheet has been found by MD simulations very advantageous for extremely high water flux rates and very efficient salt rejection Owing to its hydrophobic surface properties, FG found application for anti-corrosion and self-cleaning coatings FG has also found applications in the field of biomedicine. In 2012, Wang et al. Finally, in 2012, two independent reports appeared studying the non-linear optical properties of FG 6Fluorographene displays sharply different properties than graphene because it lacks conjugated network of π-conjugated electrons, which makes this material a wide band gap insulator. Fluorographene was born rather recently, because it was isolated in 2010, but its bulk parent graphite fluoride has been known for more than one hundred years and since the seventies GrF has been used as industrial lubricant. The industrial usage of GrF makes also easily available FG, which can be prepared from GrF by exfoliation technologies. Despite its youth, FG found several important applications in coating, batteries, separation technologies, and electrochemical sensing. Recent discoveries documenting high-reactivity of FG open new doors to a wide range of graphene derivatives. Chemical transformation of FG is easy and scalable and leads to high-yield and selective covalent graphene derivatives, like cyanographene and graphene acid. Such graphene derivatives enable reactive functional groups homogeneously distributed over the graphene surface, which can be further utilized for covalent grafting of other functionalities, e.g., carbon dots, biomacromolecules, polymers etc., to graphene. Such graphene derivatives may also function as a versatile platform for countless applications, e.g., in selective electrochemical sensing, light harvesting, catalysis etc., therefore a significant attention should be paid to synthesis and testing of these materials. The chemical processability, high-thermal stability, low surface energy, and availability make FG an extraordinary material among other 2D materials, because its properties can be turned into numerous marketed technologies in the near future.


The analogue of electromagnetically induced transparency in optical ways has shown great potential in optical delay and quantum-information technology due to its flexible design and easy implementation. The chief drawback for these devices is the bad tunability. Here we demonstrate a tunable optical transparency system formed by graphene-silicon microrings which could control the transparent window by electro-optical means. The device consists of cascaded coupled ring resonators and a graphene/graphene capacitor which integrated on one of the rings. By tuning the Fermi level of the graphene sheets, we can modulate the round-trip ring loss so that the transparency window can be dynamically tuned. The results provide a new method for the manipulation and transmission of light in highly integrated optical circuits and quantum information storage devices. Since it has been proposed, the electromagnetically-induced transparency (EIT) effect has shown great potential in various applications, including slow light control, quantum information processing and sensing technology124567891078Graphene, a new material that has been available for only a decade, has generated great interest due to its exceptional properties such as high carrier mobility14161720222324In this work, we propose and experimentally demonstrate the EIT-like effect on graphene-silicon cascaded micoring resonators in which the transparency peak can be dynamically tuned via electrically control. By applying increasing voltage to the graphene/graphene capacitor which has been covered on one of the ring waveguides, regular changes of the EIT-like spectrum have been observed.EF), which will in turn alter the rate of interband transitions and, subsequently, the optical transitionsThe structure of our device is depicted in 2O3 was employed to prevent potential carrier injections from the bottom graphene layer into the silicon2 upper cladding were deposited are shown in 2O3, obtained using the same ALD method. To apply voltage to the capacitor Ti/Au (10/100 nm) contacts were used for both layers of graphene by electron-beam evaporation. We then provided 1 μm-thick SiO2 upper cladding deposited by plasma-enhanced chemical vapor deposition to avoid the loss caused by metal contact.The device was fabricated on commercial SOI wafers, having a silicon thickness of 220 nm and a buried-oxide thickness of 3 μm. The bus waveguide and the two cascaded ring resonators were fully etched, with the depth of 220 nm and a width of 450 nm, to guide single-mode transverse electric (TE) light . The radVb is added, the change of the carrier concentrations in graphene can be expressed asV0 is the offset voltage caused by natural doping, ε0 and ε are the permittivities of free space and of Al2O3, respectively, and t is the thickness of the Al2O3 between the two graphene layers, e is charge of the electron. Thus, the Fermi level of graphene will be shift as ħ is the Plank constant divided by 2π and vF is the Fermi velocity. When the bias voltage dependent Fermi level EF(Vb) is close to the Dirac point, interband absorption will occur as electrons are excited by the incoming photons (EF(Vb) is greater than half of the photon energy of incident light  of the graphene-silicon waveguide, which is mainly decided by the Fermi level-dependent dielectric constant (εg) of graphene. The dielectric constant εg can be obtained through ω is the frequency, tg is the thickness of the graphene layer, and σ is the optical conductivity of graphene. The overall mode in the graphene-silicon waveguide displays a Gaussian distribution. The graphene layers only capture very few portions of the fields and the fields outside the graphene layer cannot feel εg variationsεg′) of graphene which changes with the voltage-dependent Fermi level and is similar to the resonance frequency shifts observed in optical plasmon resonance with grapheneThe tunability of the graphene-ring resonator based EIT-like device is investigated by applying different bias voltages. For zero bias voltage, Fermi level is closed to the Dirac point and the top ring has relative high loss and the EIT-like effect is consequently weak , correspεg′ and εg″, of graphene can be obtained from its optical conductivity (σ), which can be derived from the Kubo formula in a complex form consisting of interband and intraband contributions2930The real and imaginary parts of the complex dielectric constant, τ2 is the relaxation time associated with electron interband relaxation and cooling of hot phonons313233τ2 has been measured on a picosecond scale33neff is proportional to graphene’s dielectric constant εg in both real and imaginary partsneff) represents the loss in the waveguide and it is the same for neff) which has a proportional relationship with the wavelength shift of the transmission curve (EF(Vb) and so does Re(neff), so the transparency curve has a red shift (EF(Vb) and so does Re(neff), so the transparency curve has a blue shift  at this voltage. Furthermore, the red and blue shifts of the transparency window have been well explained in terms of the real part of the dielectric constant of graphene. Our results will provide important guidelines for the design and use of tunable optical EIT devices which have promising applications in slow light, quantum information processing and sensing technology, and provide a new method for the manipulation and transmission of light in highly integrated optical circuits. Furthermore, compare with the mechanical tuning of the EIT-like effect, the tuning speed of the device could be as high as the one obtained with modulators2223242O3 was used to prevent potential carrier injections from the bottom graphene layer into the silicon. 200 nm thick polymethyl methacrylate (PMMA) was spin-coated onto the graphene sheet which was grown by chemical vapour deposition (CVD) on Cu film and baked at 200 °C for 1 min. The copper foil was then removed using FeCl3 solution and the graphene sheet, coated with PMMA, was transferred onto the device. Finally, the PMMA was removed using acetone and the residue was rinsed with isopropanol to obtain a clean graphene surface. To remove the unwanted part of graphene, the deep-ultraviolet lithography and oxygen plasma were used. Before deposing the sandwich 20 nm Al2O3, 10 nm Ti and 50 nm Au were deposited by electron-beam evaporation and patterned by a lift-off process. This was done to protect the bottom graphene from the sandwich Al2O3 etching process for electric contacting. Owing to the hydrophobic nature of the graphene basal plane, it is difficult to depose Al2O3 directly on it. For this reason, before deposing Al2O3, a 1 nm aluminum layer was evaporated using electron-beam evaporation and immediately oxidized into Al2O3 in ambient air2O3 as the seed layer, the sandwich Al2O3 was then deposited on the device. In order to contact the electrode with the bottom graphene layer, which was fully covered by Al2O3, reactive ion etching (RIE) was used to remove a patch of Al2O3 from the Ti/Au (10/50 nm) which had been previously deposed. The transfer procedures used for top graphene layer was the same with the bottom one. The final device was then covered with 1 μm-thick SiO2 deposited by plasma-enhanced chemical vapor deposition (PECVD) and drilled by RIE to contact the two graphene layers with the electrode.The cascaded ring waveguides were fabricated in the SOI wafer with a silicon thickness of 220 nm and a buried-oxide thickness of 3 μm. E-beam lithography (EBL) and inductively coupled plasma (ICP) etching were used to fabricate the 220 × 450 nm waveguides and the 300 × 300 nm gratings. The region for graphene transfer (the etching era for the top ring) was broadened to obtain a good coverage of graphene. Before the transfer of the bottom graphene, 5 nm isolation layer deposited (ALD) AlHow to cite this article: Wang, Y. et al. Tunable optical analog to electromagnetically induced transparency in graphene-ring resonators system. Sci. Rep.6, 38891; doi: 10.1038/srep38891 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


In-depth study of the intron retention levels of transcripts provide insights on the mechanisms regulating pre-mRNA splicing efficiency. Additionally, detailed analysis of retained introns can link these introns to post-transcriptional regulation or identify aberrant splicing events in human diseases.e.g. U12-type vs U2-type) and its plotting functions allow visualization of the distribution of the retention levels of the introns. Statistical methods are adapted from the DESeq2, edgeR and DEXSeq R packages to extract the significantly more or less retained introns. Analyses can be performed either sequentially (on single core) or in parallel (on multiple cores). We used IntEREst to investigate the U12- and U2-type intron retention in human and plant RNAseq dataset with defects in the U12-dependent spliceosome due to mutations in the ZRSR2 component of this spliceosome. Additionally, we compared the retained introns discovered by IntEREst with that of other methods and studies.We present IntEREst, Intron–Exon Retention Estimator, an R package that supports rigorous analysis of non-annotated intron retention events (in addition to the ones annotated by RefSeq or similar databases), and support intra-sample in addition to inter-sample comparisons. It accepts binary sequence alignment/map (.bam) files as input and determines genome-wide estimates of intron retention or exon-exon junction levels. Moreover, it includes functions for comparing subsets of user-defined introns (ZRSR2 gene. Intron retention events caused by ZRSR2 mutation that we discovered using IntEREst (DESeq2 based function) show considerable overlap with the retained introns discovered by other methods (e.g. IRFinder and edgeR based function of IntEREst). Our results indicate that increase in both the number of biological replicates and the depth of sequencing library promote the discovery of retained introns, but the effect of library size gradually decreases with more than 35 million reads mapped to the introns.IntEREst is an R package for Intron retention and exon-exon junction levels analysis of RNA-seq data. Both the human and plant analyses show that the U12-type introns are retained at higher level compared to the U2-type introns already in the control samples, but the retention is exacerbated in patient or plant samples carrying a mutated The online version of this article (10.1186/s12859-018-2122-5) contains supplementary material, which is available to authorized users. Alternative pre-mRNA splicing is a cellular process in eukaryotes that generates multiple transcripts from a single gene. Of the various types of alternative splicing (reviewed by Hamid and Makeyev ) intron e.g. U4atac and U12 snRNAs, U11/U12-65K and ZRSR2 proteins) show, among other splicing defects, a further increase in IR levels of the U12-type introns [A well-established example of IR involves U12-type introns , which are spliced less efficiently compared to the U2-type (major) introns . The cla introns –19.i.e. Intron–Exon Retention Estimator that is based on the intron retention analysis used in Niemelä et al. [e.g. differential intron retention test based on the “exon usage test” provided by DEXSeq [p-values based on the null hypothesis that IR does not vary across the analyzed sample groups. The resulting p-values estimated for each intron allow subsequent identification of introns that show statistically significant difference of IR between the sample groups. IntEREst also provides tools for plotting the distribution of retention levels of the introns of interest within single or multiple samples. In addition, large datasets that demand significant computation time can be analyzed in parallel on multiple computing cores. IntEREst is available as a Bioconductor package and together with the manuals are accessible through https://bioconductor.org/packages/release/bioc/html/IntEREst.html.Various alternative splicing analysis tools have been developed –22, howeä et al. . IntEREsä et al.  values ay DEXSeq , 26, dify DEXSeq , or exacy DEXSeq , 29. Thee.g. U12-type and U2-type introns.IntEREst is an R package that supports various functions to measure the retention levels of the introns, perform statistical differential intron retention analysis across various samples, and plot the distribution of retention levels of different types of introns across various samples. The main design aim of IntEREst has been to support analysis of relative low level IR values (>10%) that are more challenging to implement with the existing software  but are i.e. interest and interest.sequential) accept a .bam read alignment file and a reference as inputs, and output the raw  and normalized number of fragments mapping to each exon or intron. The reference includes coordinates of exons and introns together with their annotations, such as gene and transcript names, and intron type identifier. The reference can be built using the referencePrepare function supported by IntEREst. Note that the intron identifiers used in our analysis are U12- and U2-type introns, but the application of IntEREst is not limited to the comparison of these intron types. Other classifications can be defined by the user and the retention levels of the introns can be plotted and compared across the user-defined classes. The functions in the IntEREst package that are specific to the comparisons of the U2- vs U12-type introns, e.g. u12Boxplot, u12DensityPlot, u12Index start with “u12”.The RNAseq read summarization functions  interest.sequential, that runs sequentially on a single computing core. These functions use the bpiterate function from the BiocParallel R Bioconductor package [m reads at a time (by default m = 1 million) to comply with the limitations of the memory usage in the running environment. When running interest.sequential, the mapped reads are analyzed as batches of m reads (or read pairs if the isPaired parameter is set TRUE) at a time on a single computing core. With interest it is possible to analyze n batches of m reads (i.e. m×n reads or read pairs) simultaneously while they are distributed over n computing cores and repeat this process until all reads have been analyzed.IntEREst features two functions that estimate the raw and normalized intron retention levels: 1)  package  to read interest.sequential and interest support two distinct analysis modes: 1) intron-exon junction estimation and 2) exon-exon junction estimation. It is possible to configure the analysis to include only the reads that map to intron-exon or exon-exon junctions, however with default settings reads that map entirely to the intronic or exonic regions are also included in the calculation of retention level estimates. For a typical intron-exon junction estimation analysis, we recommend to collapse the overlapping exonic coordinates across various splicing isoforms in the reference to avoid any biases in the IR calculation that may be introduced by the read counts of alternative exons, or by exonic regions overlapping with sequences annotated as introns in other transcripts. To improve the running time and avoid repetitive processes, in exon-exon junction analysis mode, we recommend using a filtered reference resulting from the unionRefTr function. This function identifies all repeating exons and uses only a single copy of each. Moreover, because repetitive sequence elements may bias the read mapping and thus affect the IR estimates, the read summarization functions support the possibility to exclude the repeat regions and reads that map to such regions. The default normalization method applied in the read summarization functions is Fragments Per Kilobase per Million mapped fragments (FPKM) however, it is scaled at transcript level (formula 1). For every intron i of gene g with I introns, if the length of the intron is Lig and the number of fragments mapped to the intron is Xig its normalized retention value will be FPKMig:The summarization functions lfc that estimates the log2 FC of the retention levels across two various conditions, moreover it includes a function psi to measure the Ψ values, i.e. the percent spliced in, for all studied introns. We have adapted several statistical tests from multiple sources for intron retention and exon-junctions analysis: DESEq2 [i.e. DEXSeqInterest function) differs from the others as it uses the differential exon usage method to perform gene-wise comparisonsIntEREst provides a function : DESEq2 , edgeR [: DESEq2 , 22, and: DESEq2 , 26. AllZRSR2 gene that encodes an integral protein component of the minor spliceosome. Moreover, the original analysis of the dataset reported that the ZRSR2 mutations in the patient samples led to increased retention of primarily U12-type introns while the U2-type introns were reported to be less affected [ZRSR2 gene (referred to as ZRSR2mut), 4 were diagnosed with MDS but lacked the ZRSR2 mutations (referred to as ZRSR2wt), and 4 were healthy individuals (HEALTHY).To demonstrate the application of IntEREst in comparing retention levels of various types of introns across several samples, we reanalyzed the RNAseq data from myelodysplastic syndrome (MDS) patients and control subjects included in Madan et al.  study. Saffected . The datannotateU12 function that uses Position Weigh Matrices (PWM) extracted from the U12DB database [interest function. Initially, by using the interestResultIntEx function a result object was built that includes information of both intron retention and exon-exon junction levels . Of the 510 U12-type introns in the data, 269 (i.e. 52.7% of the U12-type introns) showed significant up-regulation of IR in the ZRSR2mut samples when compared to the controls, while none of the U12-type introns showed a significant reduction in IR . Rather, the median log2 fold-change of the U2-type introns was approximately zero whereas the median log2 fold-change of U12-type introns was ~1.5  for all U12-type introns was about 1% as compared to 0.6% with U2-type introns  and 6 samples (3 roots and 3 shoots referred to as RGH3wt) that lack the mutation. The results of the Maize data analysis mirror our findings with the MDS data. Analogous to MDS data, the RGH3mut samples showed increased IR with ~46% of U12-type introns, while only a ~0.46% of the U2-type introns showed an increase in IR  in the recognition of U12-type introns [Together, our results suggest that IntEREst provides reliable quantification of differential IR events; Specifically, our results are not only consistent with the well-documented increased retention levels of U12-type introns , 11, 31, introns , 34.i.e. dedicated software for IR analysis. Note that all comparisons described in the following are based on the introns that were available in the both references used by the compared counterparts.We evaluated the performance of the IntEREst in two ways using the MDS benchmark dataset. First, we carried out internal analysis comparing IntEREst results in conjunction with different statistical analysis packages implemented in IntEREst. Subsequently, we carried out comparison with both, the published results of the MDS analysis  and IRfii.e. DESeq2, GLM function of edgeR and DEXSeq, referred hereafter as IntEREst-DESeq2, IntEREst-edgeR and IntEREst-DEXSeq, respectively. The DESeq2 and edgeR have been previously reported to result in somewhat dissimilar results in differential gene expression analysis [interest in its two running modes) using interestResultIntEx. Subsequently, we used deseqInterest and glmInterest functions (i.e. the IntEREst functions based on DESeq2 and edgeR-GLM) to analyze the change of IR relative to the change of the junction levels of their flanking exons. We used an adjusted p-value  threshoWe found that there is a significant overlap both with upregulated and downregulated introns between the IntEREst-DESeq2 and IntEREst-edgeR Fig , with a Comparison of the IntEREst-DESeq2 to IntEREst-DEXSeq revealed a considerable overlap between the two methods Fig. . Howeveri.e. 235) overlapped with the introns discovered by the IntEREst-DESeq2  of the significant IR events reported by Madan et al. [We further compared our IR results with the original analysis of the MDS dataset by Madan et al. . We founTogether, our results revealed that the different methods implemented in IntEREst are able to identify a highly overlapping set of high-confidence differentially retained introns. Additionally, each method also identified IR events that are unique to a particular method. This provides the flexibility to select an approach best fitting to the particular research questions.i.e. DESeq2Interest ) and repeated this 10 times. As expected, the results reveal that increasing numbers of biological replicates lead to a discovery of an increased number of statistically significant IR events  in each sample, followed by analysis with IntEREst-DESeq2. In our analyses we assumed that the quality and read coverage is equal in all the individual MDS datasets. As a result, we observed that an increase in the sequencing library size leads to a discovery of increasing numbers of introns showing statistically significant deviation in the IR levels. However, the slope of increase of the number of discovered IR events decreases and levels off at the highest library sizes  used in this study is not sufficient to estimate the optimal required for IR discovery, we note that library sizes with more than 35M mapped reads start to approach the point where the improvements in detecting novel IR events are marginal. In sum, we believe that IntEREst is a reliable tool in R/Bioconductor environment for detailed intron retention analysis of RNAseq datasets.IntEREst is implemented as an R package freely available at the Bioconductor repository.Project name: IntEREstArchived version: 1.2.2https://github.com/gacatag/IntEREst/Project home page: https://bioconductor.org/packages/release/bioc/html/IntEREst.htmland Operating system(s): Platform independentProgramming language: ROther requirements: R v 3.4 or higherLicense: GPLAny restrictions to use by non-academics: No restrictionsAdditional file 1:HTML file including all the running scripts and supplementary figures and tables. (HTML 789 kb)Additional file 2:Tab delimited text file that includes the differentially retained introns, when comparing the ZRSR2mut samples to the controls using the IntEREst-DESeq2. (TSV 634 kb)


Dear Editor,Blockade of PD-1/PD-L1 signaling pathway by monoclonal antibodies (MAbs) to release the anti-tumor activity of pre-existing tumor specific T cell immunity has initiated a new era for tumor immunotherapy. Administration of anti-PD-1 MAbs (nivolumab and pembrolizumab) in either monotherapy or in combination with anti-CTLA-4 MAbs or traditional chemotherapy has achieved a tumor regression rate of 30%–50% in dealing with melanoma, non-small cell lung cancer, etc. . Subsequently, crystal screen was performed with the durvalumab-scFv/PD-L1 complex proteins, and well-diffractable crystals grew in 3.5 mol/L sodium formate, pH 7.0 (See more details in supplementary information).In the present study, we expressed the two-Ig-domain PD-L1 and single chain Fv fragment (scFv) of durvalumab as inclusion bodies in The complex structure of durvalumab-scFv/PD-L1 was determined by molecular replacement at a resolution of 2.3 Å (Table S1). The binding of durvalumab to PD-L1 involves both of its heavy chain (VH) and light chain (VL)  and the durvalumab-scFv/PD-L1 complex was conducted to elucidate the molecular basis of durvalumab-based PD-1/PD-L1 intervention. The binding of durvalumab to PD-L1 shows a stereo clash with that of PD-1 Fig. . The comKD = 0.667 nmol/L, 1.75 nmol/L, and 0.83 nmol/L, respectively  and/or dissociation rate constant  compared to that of durvalumab  and atezolizumab . On the other hand, the binding affinity of avelumab to PD-L1 is much higher than the other three MAbs (KD = 0.0467 nmol/L) with highest Ka and lowest Kd value (Table S3). Taken together, the binding kinetics of durvalumab is much similar to that of atezolizumab, while binding properties of BMS-936559 and avelumab are distinct from the above two MAbs. The differential binding profiles of these anti-PD-L1 MAbs would have profound effects on their pharmacokinetics. However, whether the distinct binding epitopes and kinetics of these MAbs would affect therapeutic efficacy remains to be elucidated. Escape from anti-PD-1 or anti-PD-L1 could be induced from multiple aspects, including selection of poor-immunogenic tumor cells, immune evasion via up-regulation of alternative inhibitory molecules, etc.  under accession code 5XJ4.Atomic coordinates have been deposited in the Protein Data Bank  and the National Basic Research Program (973 Program) (NO. 2013CB531502). We also thank Yuanyuan Chen and Zhenwei Yang from Institute of Biophysics, Chinese Academy of Sciences for their technical support in the SPR assay. G.F.G. is a leading principle investigator of NSFC Innovative Research Group (Grant No. 81621091).Supplementary material 1 (PDF 371 kb)Below is the link to the electronic supplementary material.


Idiopathic pulmonary fibrosis (IPF) is a devastating disease of unknown etiology. The pathogenic mechanisms are unclear, but evidence indicates that aberrantly activated alveolar epithelial cells secrete a variety of mediators which induce the migration, proliferation and activation of fibroblasts and finally the excessive accumulation of extracellular matrix with the consequent destruction of the lung parenchyma. CC16 (approved symbol SCGB1A1), a putative anti-inflammatory protein produced by “club” cells in the distal airways, has not been evaluated in IPF lungs. In this study, we determined the serum and bronchoalveolar lavage (BAL) levels as well as the lung cell localization of this protein. Also, we explored the usefulness of serum levels of CC16 for the differential diagnosis of IPF (n = 85), compared with non-IPF interstitial lung diseases [chronic hypersensitivity pneumonitis  and connective tissue diseases ]. CC16 was significantly increased in serum and BAL fluids of IPF patients and was found not only in club cells but also in alveolar epithelial cells. When compared with non-IPF patients and controls, serum levels were significantly increased (p<0.0001). Sensitivity and specificity for CC16 (cut-off 41ng/mL) were 24% and 90%, positive predictive value 56% and negative predictive value 69%. These findings demonstrate that CC16 is upregulated in IPF patients suggesting that may participate in its pathogenesis. Although higher than the serum levels of non-IPF patients it shows modest sensitivity to be useful as a potential biomarker for the differential diagnosis. Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and usually lethal fibrosing interstitial pneumonia of unknown etiology and a median survival of 2–3 years after diagnosis . IPF occThe pathogenic mechanisms have not been elucidated, but a growing body of evidence indicates bronchoalveolar epithelial cells play a key role in the initiation and perpetuation of the disease. These epithelial cells are highly active and secrete a variety of growth factors, cytokines, chemokines, matrix metalloproteinases and coagulation factors that participate in the formation of the fibroblastic/myofibroblastic foci and the subsequent abnormal tissue remodeling . In thisIn addition, we aimed to determine whether serum concentration of CC16 may distinguish IPF patients from those with some non-IPF interstitial lung diseases (ILD) that may also present an UIP-like pattern. Actually, it is well known that a UIP-like pattern may be found in other fibrotic lung diseases mainly in some connective tissue-diseases (CTD-ILD) , 6 and cA variety of biomarkers related to alveolar epithelial cell dysfunction or fibroproliferation and matrix deposition has been described in IPF , 13, butIn this context, the aim of this study was to assess the expression and lung localization of CC16 in IPF lungs and its diagnostic value to distinguish IPF from non-IPF patients.The concentration of CC16 in serum and bronchoalveolar lavage fluids was performed using samples already obtained and maintained at -70°C from a population of IPF and non-IPF patients attending the Interstitial Lung Disease Clinic of the National Institute of Respiratory Diseases in the last 8 years. Our serum bank comprises 502 patients with IPF, 651 patients with cHP, and 287 patients with CTD-ILD. From this population, 85 patients from each group were randomly selected for quantification of serum CC16. In the CTD-ILD group, only patients with rheumatoid arthritis or Sjögren syndrome were included. Diagnosis of each disease was performed according to accepted international criteria –17. PatiDemographic information was obtained from all patients , medical history , physical examination, respiratory function tests  and changes in oxygen saturation in the 6-minute walk).All blood samples were obtained on fasting and after at least 10 minutes rest, to control the postural effects on blood measurements. Samples were aliquoted and frozen, and thawed only once before measurement CC16. The quantification of CC16 was performed by ELISA, by duplicate, according to the manufacturer's instructions using the Human Cell Protein Club kit, .As part of the diagnostic process, bronchoalveolar lavage (BAL) was achieved as described . Briefly2O2 was used as substrate. The experiments included controls in which the primary or secondary antibody was omitted.Cell localization of CC16 was performed in lung biopsies of IPF patients and controls tissues as previously described . BrieflyImmunofluorescence staining was performed in 3μm thick tissue sections adhered to silanized slides. After heat-induced antigen retrieval, samples were permeabilized and blocked in a single step incubating them for 30 minutes in PBS with 2% normal pig serum and 0.5% Triton X-100  at room temperature (RT). Afterwards samples were washed and incubated at 4°C overnight with the primary antibodies: anti-CC16  and anti-prosurfactant Protein C . After incubation, samples were washed and incubated with fluorescent secondary antibodies  for 1 hour at RT. Samples were mounted with ProLong Gold mounting media (Life Technologies). All experiments included controls with/without primary antibody or with/without secondary antibody. Image capture was done with an FV-1000 confocal laser scanning microscope  in sequential scanning mode to image each fluorochrome individually.Results were collected in Excel and analyzed in the Stata statistical package, version 11. Results are expressed as mean with standard deviations. An exploratory data analysis was performed to identify inconsistent data entry errors. Univariate analysis of each variable was done to calculate the measures of central tendency and dispersion of continuous variables and proportions for categorical variables. In bivariate analysis, mean differences and proportions according to each group were calculated and Mann-Whitney U test and ANOVA were applied. We defined p value <0.05 as statistical significant difference. Receiver operating characteristic (ROC) curve was generated to determine the sensitivity threshold (Y axis) and 1-specificity (X axis) of CC16. The area under the curve (AUC) was used to compare and determine the power of discrimination of CC16 to diagnose IPF. Likewise the positive and negative predictive values of serum CC16 as biomarker were determined. Multivariate linear regression model and Spearman correlation was used to assess the association between CC16 (dependent variable) and relevant demographic and functional independent variables .Eighty five patients with IPF, 170 non-IPF patients (85 cHP and 85 CTD-ILD), and 30 healthy individuals were included in this study. Demographic characteristics and lung function data are shown in CC16 was found significantly higher in IPF compared with non-IPF patients and healthy controls . Serum lTo determine the potential for diagnostic use of CC16 as biomarker, we applied ROC analyses . AccordiWe also correlated the concentrations of CC16 with the severity of baseline FVC and DLCO, which have been associated with the prognosis of IPF. However, no significant correlations were observed (data not shown). To determine whether the increase of CC16 was independent of demographic and functional variables, a multivariate linear regression model including gender, smoking, FVC, DLCO, and oxygen saturation at rest was constructed. The increase of CC16 was independent of these variables.As illustrated in The cellular localization of CC16 in the lungs of patients with IPF has not been previously evaluated. For this purpose, samples from IPF and normal lung tissue sections were examined by immunohistochemistry and immunofluorescence. As illustrated in IPF is a devastating and highly lethal disease, of uncertain pathogenesis. In the last 15 years, the pathogenic paradigm for IPF has moved from one of unresolved chronic inflammation toward one of alveolar epithelial cell dysfunction that results in the over-expression of almost all the mediators responsible of fibroblast migration, proliferation and activation, and tissue remodeling , 20, 21.In this study, we revealed by the first time that CC16 is also expressed by these epithelial cells in IPF lungs and that is markedly increased in serum and bronchoalveolar lavage fluids obtained from these patients. In addition, serum concentration of CC16 was significantly increased in IPF patients compared with the levels observed in non-IPF disorders, cHP and CTD-ILD, two diseases where immunopathological and inflammatory processes play a critical role.CC16 (approved symbol SCGB1A1) is a member of the secretoglobin family of small secreted proteins mainly produced by club cells localized in bronchioles including terminal ones. It has been suggested that CC16 has anti-inflammatory and antioxidative properties in the lungs, and that might have a protective role against airways diseases like COPD and asthma , 23. ActHowever, our study was performed in a largest cohort of IPF patients and importantly this protein was by the first time demonstrated to be elevated in bronchoalveolar lavage suggesting a higher local production. Moreover, we also revealed that in IPF, in addition to Club cells, activated alveolar epithelial cells also contribute to its production. This is an important finding because strong evidence indicates that a dysfunctional alveolar epithelium plays a critical role in the aberrant injury/remodeling processes that occur in sporadic and familial IPF .The putative role of increased production of CC16 in these disorders is presently unknown, and may be different in inflammatory-driven (cHP and CTD-ILD) and epithelial-driven fibrosis (IPF). Therefore, increased CC16 in diverse interstitial lung disorders may indicate its participation in different processes including an insufficient and overwhelm defensive mechanism or may contribute to some pathogenic mechanisms. Interestingly, it has been shown that direct contact of club cells induce apoptosis of epithelial cells from distal airways and alveoli through a tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-dependent mechanism, thus affecting wound repair . HoweverHowever, the cause and effect of the increased CC16 as well as the remarkable difference observed between interstitial lung diseases, mainly IPF, and disorders that affect the airways, such as COPD, needs further investigation.Another aim of our study was to evaluate whether the serum levels of CC16 may help to distinguish IPF from non-IPF interstitial diseases. The differential diagnosis of IPF with other chronic fibrosing lung disorders that exhibit an UIP pattern may be extremely difficult , 8, 29. Molecular profiling analysis of blood serum/plasma has revealed several putative biomarkers, and evidence suggests that some of them, e.g., MMP-7 may help to predict IPF outcome. Recently, a biomarker index of SP-D, MMP-7, and osteopontin was found to enhance diagnostic accuracy in IPF patients compared to those with non-IPF interstitial lung diseases .In general, the molecular biomarkers found so far seem to reflect the aberrant activation of alveolar epithelial cells. With this in mind, we evaluated the putative role of CC16 to distinguish IPF from non-IPF interstitial lung diseases. Our results showed that although increased levels of CC16 seems to be a risk factor to IPF, the increase of this protein by itself seems to be insufficient for differentiating IPF from non-IPF patients; however, at certain levels may increase suspicion of IPF and may complement other clinical, radiological and morphological findings to improve diagnostic accuracy.The main limitation of this study is the lack of a replication cohort which limits our ability to draw definitive conclusions. The strengths of this study are the confident diagnosis of all the included cases, and the finding of alveolar contributions and local increase of CC16.S1 Dataset(PDF)Click here for additional data file.


Four patients suffering from advanced amyotrophic lateral sclerosis (ALS)—two of them in permanent CLIS and two entering the CLIS without reliable means of communication—learned to answer personal questions with known answers and open questions all requiring a “yes” or “no” thought using frontocentral oxygenation changes measured with fNIRS. Three patients completed more than 46 sessions spread over several weeks, and one patient (patient W) completed 20 sessions. Online fNIRS classification of personal questions with known answers and open questions using linear support vector machine (SVM) resulted in an above-chance-level correct response rate over 70%. Electroencephalographic oscillations and electrooculographic signals did not exceed the chance-level threshold for correct communication despite occasional differences between the physiological signals representing a “yes” or “no” response. However, electroencephalogram (EEG) changes in the theta-frequency band correlated with inferior communication performance, probably because of decreased vigilance and attention. If replicated with ALS patients in CLIS, these positive results could indicate the first step towards abolition of complete locked-in states, at least for ALS.Despite partial success, communication has remained impossible for persons suffering from complete motor paralysis but intact cognitive and emotional processing, a state called complete locked-in state (CLIS). Based on a motor learning theoretical context and on the failure of neuroelectric brain–computer interface (BCI) communication attempts in CLIS, we here report BCI communication using functional near-infrared spectroscopy —which measures brain hemodynamic responses associated with neuronal activity—could overcome this barrier. Four patients suffering from advanced amyotrophic lateral sclerosis (ALS), two of them in permanent completely locked-in state and two entering the completely locked-in state without reliable means of communication, learned to answer personal questions with known answers and open questions requiring a “yes” or “no” by using frontocentral oxygenation changes measured with fNIRS. These results are, potentially, the first step towards abolition of completely locked-in states, at least for patients with ALS.Despite scientific and technological advances, communication has remained impossible for persons suffering from complete motor paralysis but intact cognitive and emotional processing, a condition that is called completely locked-in state. Brain–computer interfaces based on neuroelectrical technology  have failed at providing patients in a completely locked-in state with means to communicate. Therefore, here we explored if a brain–computer interface based on functional near infrared spectroscopy ( Communication is the process of expressing and sharing feelings, thoughts, and intentions with one another by verbal and various nonverbal means. Communication skills appear automatic but can pose severe challenges to individuals suffering from motor neuron disorders. The most devastating of motor neuron diseases is amyotrophic lateral sclerosis (ALS) , which ifMRI) [fNIRS) [Brain–computer interface (BCI) represents a promising strategy to establish communication with paralyzed ALS patients –7, as itfMRI) , and fun [fNIRS) , to reco [fNIRS) . The fir [fNIRS) . With at [fNIRS) . Since t [fNIRS) ,16,17, s [fNIRS) –20, and  [fNIRS) –24, have [fNIRS) –27 for c [fNIRS) ,27–30. I [fNIRS) ,23, and In a meta-analysis of the scientific literature of all ALS patients in CLIS , it was Because none of the BCI techniques outlined above are able to provide viable means of communication , the patfNIRS to measure and classify cortical oxygenation and deoxygenation following the “yes” or “no” thinking of the CLIS patient in response to true or false questions, respectively. The report described a CLIS patient with ALS achieving BCI control and “yes” and “no” communication to simple questions with known positive answers or negative answers and some open questions over an extensive time period. Although it was not spontaneous and voluntary, controlled communication, it at least enabled the individual without any means of communication to transmit “yes” and “no” to questions framed by family members and/or caregivers. The result opened a venue to provide at least some means of communication to individuals in CLIS who are otherwise left communicationless. Hence, an extensive study was performed on four ALS patients in CLIS to train them to communicate “yes” and “no.” In the present study, which is the first of its kind, fNIRS-based BCI was used for binary communication in four ALS patients in CLIS. The fNIRS-based BCI was employed successfully to train patients to regulate their frontocentral brain regions in response to auditorily presented questions. After training a classifier separating “yes” from “no” answers for several days, the patients were given feedback of their affirmative or negative response to questions with known answers and open questions over weeks.A single case report by Gallegos-Ayala et al. (2014)  used fNI2Hb) during the “true/yes” and “false/no” sentences’ interstimuli interval (ISI)—which corresponds to patients’ response interval over the frontocentral brain region of patients F, G, B, and W—are shown in The relative change in oxygenated hemoglobin , shown in p > 0.05) between the true and false sentences’ ISI across each patient, as shown in t-test , as shown in 2Hb), EOG, and EEG power spectrum in response to true and false questions, obtained from the frontocentral region of the brain, across all the sessions from each patient was used to determine the SVM classification accuracy of "true/yes" and "false/no" answers. Successively, the daywise CA  of each patient was compared to the adjusted chance-level threshold (described in BCI effectiveness metric section), as shown in Figs 2Hb, EEG, and EOG signals for training sessions, while online CA is reported using only O2Hb for feedback and open question sessions because feedback was provided online only using the O2Hb signal. The answering concordance between semantically paired questions , expressed as the percentage of concordant answers over pairs' repetition, was as follows: F, 68%; G, 67%; B, 67%; W, 70%. Thus, the semantic concordance rate (SCR) ranges from 67 to 78% (see p < 0.0001), in which 50% is the SCR expectation of a random classifier.The support vector machine (SVM) classifier’s classification of true sentences as true, false sentences as false, true sentences as false, and false sentences as true was used to calculate the false positive rate (FPR) and true positive rate (TPR) for each training and feedback session and also for all the training sessions and feedback sessions separately for each patient. FPR and TPR was plotted to obtain the receiver operating characteristic (ROC) curve of the binary SVM classifier during training and feedback sessions for each patient, as shown in  78% see . Median t-test  suffering from juvenile ALS with an extremely rapid disease progression (2 y from diagnosis to CLIS) was not asked open questions because of the supposedly difficult emotional state at that early stage of BCI communication but continues to train the BCI at present.The results of ANOVA and post hoc p > 0.05). The middle-frequency bands’  spectral features comparison between sentence presentation interval and sentences’ ISI revealed some main effects of the intervals factor, as reported in p < 0.05). In patient W, a higher high-theta, low-alpha, and high-alpha bands’ mean power in the sentences’ ISI compared to the sentence presentation interval was found (ISI was synchronized compared to sentence presentation). Patient F did not show any significant difference in the middle-frequency bands’ mean power and “power variability” . See Results section of The patients showed the following stable dominant frequencies: F, 6.75 Hz; G, 6.25 Hz; B, 7 Hz; and W, 8 Hz. Power spectrum density of electroencephalographic signals corresponding to "true/yes" and "false/no" sentences’ ISI acquired from channel FC6 is shown in fNIRS classification accuracy and low-frequency bands’ (those more related to vigilance) mean power revealed some interesting results . However, in patient F, who had the longest time period in CLIS, the median of the positive averaged correlation between delta and high-theta band mean power and fNIRS classification accuracy was significantly different from zero . The low-frequency bands’ mean power distribution medians of successful and unsuccessful days  was further investigated for each patient to ascertain the difference, if any. In patient G, the low-theta band mean power of successful days was significantly smaller than that of unsuccessful days (p < 0.05). In patient B, the high-theta band mean power of successful days was significantly smaller than that of unsuccessful days (p < 0.05). This strengthens the above results of lower-frequency bands’ dominance for more unsuccessful performance. Additional details are provided in the Results section of The correlation analysis between fNIRS exceeded classification of EEG oscillations from 0–30 Hz and vertical and horizontal EOG classification. However, despite the absence of reliable eye communication in all patients as the inclusion criteria in the study and by the definition of CLIS condition, EOG classification was at some sessions, albeit rarely, above chance, mainly in patient W. Nonetheless, the inability of the social environment to perceive them and their instability and the eye tracker’s failure to use them for communication [Four patients in CLIS communicated with frontocentral cortical oxygenation-based BCI with an above-chance-level correct response rate over 70% during a period of several weeks. The performance of the binary SVM classifier across all the patients, except a few training sessions of patient B, was above chance level. None of the sessions were eliminated in the analysis, and only very few sessions had to be interrupted because of life-saving measures such as sucking saliva; thus, no bias for selecting “successful” sessions incriminates the results. Correct response rate for feedback and open questions sessions, as judged by the criteria mentioned in the Material and Methods section , exceeded 75% in three out of four patients . Patients F, G, and B answered open questions containing quality of life estimation repeatedly with a “yes” response, indicating a positive attitude towards the present situation and towards life in general, as reported in larger samples of ALS patients ,44. Repenication  preventsfNIRS responses to “yes” and “no” are different, as they are in three patients showing oxygenation increase during the answering interval (ISI) for “yes” responses with negligible topographical differences and oxygenation decrease during negative answers, again without topographical differences throughout the frontal cortical area. Only the very young patient W, with an extremely rapid course of the disease and a strong genetic variant, shows a variable fNIRS pattern with different slow oscillatory oxygenation changes between “yes” and “no” answering periods. In an animal study with nonhuman primates [The unreliable discrimination between "true/yes" and "false/no" sentences’ ISI by means of EEG signals  showed a negative averaged correlation between low-theta band mean power and accuracy , meaningFor a robust validation of the BCI binary communication system in CLIS, two main unsolved questions remain: (i) the physiological identification of the cognitive processes underlying the listening to “yes–no” questions and the answerer’s mental state and (ii) the online identification of decreased vigilance states that are detrimental (lowering performance) for BCI binary communication purposes, such as decreased alertness, drowsiness, and sleeping.fNIRS system and quantitative source analysis of the different frequency bands at different sites are necessary to clarify these questions. For the study reported here, only portable devices and a few EEG channels could be used in the interest of the bedside, home-based strategy selected. Thus, our interpretation of the EEG frequency bands’ variations remains speculative.Multielectrode EEG recordings used simultaneously with the fNIRS–BCI–system in a hybrid EEG–fNIRS–BCI, with the EEG allowing online corrections of excessive reduction of vigilance indicated by appearance of delta and low-theta periods. This new hybrid system should allow further improvement of communication in CLIS.In patients completely motionless over a period of years with restricted vision because of eye muscle paralysis and compromised vision because of drying and reduced or absent afferent input from the sensorimotor system, reduced vigilance measured with EEG and an irregular sleep–wake cycle was documented by Ramos et al. (2011)  and SoekThe results on four CLIS patients reported here allow the following conclusions:fNIRS–BCI [Even after extended CLIS in ALS spanning months and years, reliable, meaningful communication using questions requiring a mental affirmative (“yes”) or negative, rejecting (“no”) answer is possible with NIRS–BCI ,56. ThisNIRS–BCI  calculatNIRS–BCI . BecausefNIRS seems to provide better classification of patients’ answers compared to oscillatory EEG responses. The above statement of a superiority of fNIRS over EEG–BCI needs a word of caution. The EEG oscillations were analyzed using average power over the 15 s answering period, neglecting the temporal dynamics of the EEG across the answering period. Thus, any difference in the beta and/or gamma frequency range (less so in the low frequencies) that may occur at different time points of the answering period is ignored with this type of averaging. Replications of the comparisons reported here between fNIRS–BCI and EEG–BCI in CLIS should employ a more complex time-frequency analysis of the EEG signals during the course of the answering period. This kind of EEG temporal dynamics analysis should investigate, at the single-trial level, relevant frequency changes at different time delays of the mental and neurophysiological signatures of the answer. With the limited number of EEG channels and the employed bandpass filter because of the home-based BCI limitations, the covert nature of the dynamics of the mental answer, and the obvious pathology of the EEG in these patients, we had to abstain from further complex analysis. In the present study, only a preliminary EEG temporal dynamics analysis based on averaged data of each session for each patient was viable . However, because the time-frequency analysis was performed at session level , caution is necessary in the interpretation of the results. Similar difficulties encountered using different techniques are described in a previous study of patient F and two LIS ALS patients , albeit a slightly different semantic conditioning paradigm employing electrical stimulation was used. Compared to fNIRS, the EEG time-frequency analysis may identify specific neuroelectric frequencies’ oscillations at different time points with fine resolutions and with potential further insights in neurophysiological mechanisms underlying the engaged mental processes. Conversely, fNIRS signals may be more easily detected for binary classification. We have argued previously [fMRI neurofeedback experiments because of an existing feedback pathway between the vascular system in the central nervous system. While neuroelectric changes lack receptors systems of their own activity, the vascular bed provides accurate information of flow and diameter changes to the neuronal assemblies in its neighborhood. This allows adjustment to metabolic and cognitive needs and probably superior access to voluntary control [fMRI and fNIRS provides feedback to the brain about its state changes, while the neuronal neuroelectric changes may not be “perceived” by the brain and thus provide no feedback of its present state or state changes; thus, a physiological system should be superior for instrumental learning. To put it more colloquially: physiological feedback of our thoughts (“perceiving thoughts”) is encoded in the neuronal control structures of the brain through the vascular systems and not through neuromagnetic changes such as cellular membrane polarization changes and changes in neuroplastic synapses. While thoughts probably consist of neuroelectric changes and their underlying cellular polarization across the cell membranes, their physiological consequences or correlates may appear as metabolic. Thus, coregistration of fNIRS and EEG and other neuroelectric changes and oscillations from multiple sites maybe important in CLIS in order to monitor and eventually modify nonfavorable vigilance changes reflected in the EEG, with arousal stimulating activities to improve NIRS classification.eviously  the spec control , as requThe Internal Review Board of the medical faculty of the University of Tubingen approved the experiment reported in this study, and the patients’ legal representative gave informed consent for the study with permission to publish the results and show the face of patients in the publication. The study was in full compliance with the ethical practice of medical faculty of the University of Tubingen. The clinical trial registration number is ClinicalTrials.gov Identifier: NCT02980380. At the time of this study, prospective clinical trial registration was not mandatory for nonpharmacological studies; it was therefore registered retrospectively.fNIRS system, NIRSPORT (NIRX), which performs dual-wavelength (760 nm and 850 nm) CW near-infrared spectroscopic measurement at a sampling rate of 6.25 Hz, as shown in in A continuous wave (CW)-based Patient F  was diagnosed with bulbar sporadic ALS in May 2007, was diagnosed as locked-in in 2009, and was diagnosed as completely locked-in May 2010, based on the diagnoses of experienced neurologists. She has been artificially ventilated since September 2007, fed through a percutaneous endoscopic gastrostomy tube since October 2007, and is in home care. No communication with eye movements, other muscles, or assistive communication devices was possible since 2010. Further details of this patient are described in Gallegos-Ayala et al. (2014) .Patient G  was diagnosed with bulbar ALS in 2010. She lost speech and capability to walk by 2011. She has been fed through a percutaneous endoscopic gastrostomy tube since September 2011, artificially ventilated since March 2012, and is in home care. She started using assistive communication devices employing one finger for communication in February 2013. Later, she was diagnosed with degeneration of vision because of cornea defects in September 2013. After the failure of the finger-communication device, an attempt was made to communicate using eye tracking in early 2014. She stopped communicating with the eye in August 2014, before the BCI was introduced, and an attempt was made to communicate with the subtle twitch of an eye lid, which was not reliable. The husband and caretakers declared no communication with her since August 2014.Patient B  was diagnosed with nonbulbar ALS in May 2011. He has been artificially ventilated since August 2011, fed through a percutaneous endoscopic gastrostomy tube since October 2011, and is in home care. He started communicating with a speech device in his throat from December 2011, which ultimately failed, and he started using the MyTobii eye-tracking device in April 2012. He was able to communicate with MyTobii until December 2013, after which the family members attempted to communicate by training him to move his eyes to the right to answer “yes” and to the left to answer “no,” but the response was variable. No communication was possible since August 2014.Patient W  was diagnosed with juvenile ALS in December 2012. She was completely paralyzed within half a year after diagnosis and has been artificially ventilated since March 2013, fed through a percutaneous endoscopic gastrostomy tube since April 2013, and is in home care. She was able to communicate with eye tracking from early 2013 to August 2014 but was unable to use the eye-tracking device after the loss of eye control in August 2014. After August 2014, family members were able to communicate with her by training her to move her eyes to the right to answer “yes” and to the left to answer “no” questions until December 2014. In January 2015, eye control was completely lost, she tried to answer yes by twitching the right corner of her mouth, that too varied considerably, and parents lost reliable communication contact.All four patients reported in this manuscript were enrolled consecutively. Patients’ family approached us to get enrolled in the study because of the past work and public appearance of the corresponding author. Patients were never screened and excluded for this study. The only criterion for the inclusion in this study was that the patient should be in completely locked-in state (CLIS) or on the verge of CLIS, and family members could not communicate with eye movements or any other response with the patient. The CLIS state was then verified with confirmation of the attending neurologist, EOG recordings, and video recordings of the families’ failures to achieve contact with the patient.fNIRS and EEG data during BCI sessions is shown in The schematic depicting the experimental procedure, acquisition, and analysis of An auditory paradigm was employed to (a) train patients on questions with known answers, termed as training sessions; (b) give feedback on questions with known answers, termed as feedback sessions ; and (c) answer open questions, termed as open question sessions (“You have back pain”). Known questions are personal questions based on patient’s biography. For every known question with a clear “yes” answer, a semantically related question with a clear “no” answer was constructed and vice versa; for example, “You were born in Berlin” and “You were born in Paris.” Patients were asked to think “yes” or “no” answers and, if possible, also to use their previously successful eye movements. They were explicitly instructed not to imagine the answer or visually or auditorily imagine the word  “yes” or “no”. Open questions are general questions related to quality of life and questions of caretakers whose answers can only be known by the patient. A total of at least 200 known questions and 40 open questions were constructed for each patient with family members before the initiation of the BCI study. Each patient was visited for 4 to 5 d in a month, except patient W. Three to four sessions were performed each day depending upon the health condition reported by the caretakers of the patient. Every session lasted for 9 min, and a session in progress was terminated extremely rarely . In such a rare event, the session was started again. Since each session lasted for 9 min, the caretaker or the family member was always instructed to take care of the needs of the patient before the start of the session, and the session was always started with the permission of the caretaker or the family member. A session, once in progress, was never terminated for patients F, G, and W. For patient B, a session was terminated while in progress three times because of removal of saliva, and the data were not included in any kind of analysis.fNIRS feature necessary to differentiate between “yes” and “no” answers during ISI was extracted and classified. Only training sessions were performed during the first few days, and upon several successful training sessions (as described below in BCI effectiveness metric section), the online feedback session was performed. During training sessions, both the patient and the algorithm were trained. Patients learned to mentally answer the question, and the algorithm learned to classify the “yes” and “no” fNIRS pattern of a particular patient. This kind of “mutual learning” seems important to optimize the “yes” versus “no” classification outcome and to customize and/or adapt the BCI system to each individual patient. At the end of each training session with 20 sentences (questions), patients were told the average classification accuracy of the session  to motivate and help patients in learning. In the course of an online feedback session, patients were presented the known questions as described above, but now at the end of the 15 s ISI they were given auditory feedback of accuracy, during which the computer said, “Your answer was recognized as yes” or “Your answer was recognized as no” depending upon the question . Feedback to strengthen the conditioned response was provided only if the classification accuracy was greater than the chance-level upper limit to guide the conditioned learning toward meaningful answers and to avoid frustration by negative feedback already at the beginning of a daily session. Feedback was driven by the fNIRS classifier, calculated using the data acquired during the training sessions. After successful training and feedback sessions, the patients were presented with open questions, during which they were always given the auditory feedback of their answer.Acoustically presented instructions about the procedure were given repetitively before each training, feedback, and open questions sessions, allowing patients to recall and consolidate the required task to listen and answer mentally. Each BCI session started with training sessions, during which the patients were instructed to listen to 20 personal questions (with known answers) consisting of 10 true and 10 semantically equivalent false sentences. The sentences were presented randomly in such a way that two semantically related questions never played one after another. Family members were always present throughout the BCI session, and they never prompted the patient to answer the question. Complete pin-drop silence was maintained during the session, and only the recorded sentences were presented via audio presentation software connected to sound box with the voice of a family member or caregiver. Patients were asked to think “ja, ja…” (German for “yes”) and “nein, nein…” (German for “no”) for 15 s during the ISI until they heard the next sentence after an interval of 5 s of rest, as shown in The validity of answers to open questions can only be estimated by (a) face validity ; (b) stability over time; (c) external validity, estimated by family members and caretakers; and (d) internal validity between questions . The binary BCI system effectiveness and robustness depends on its capability of correctly classifying the neurophysiological correlates of “yes” and “no” answers to true and false questions. The proposed true and false questions have two possible outcomes only, which are equally distributed with a probability of 0.5. To ensure that the classification of “yes” and “no” answers is not at chance-level, a reliable metric has to be used. Based on binomial distribution theoretical background, Müller-Putz et al.  defined fNIRS data was acquired online throughout all the sessions, namely training, online feedback, and open question sessions. The fNIRS data acquired online was normalized, filtered using different bandpass filters (0.0016–0.3), (0.01–0.3) and (0.02–0.3) and processed using modified Beer–Lambert law [2Hb) and deoxyhemoglobin (RHb). The choice of bandpass filter had no effect on the waveforms of signal. The relative change in O2Hb computed online during each session was used to train a SVM classifier model. The mean of relative change in O2Hb across each channel was used as a feature to train the SVM model through a 5-fold cross-validation procedure. In this study, only the relative change in O2Hb was used, as after the end of sessions with known answers it was observed that O2Hb provided stable and higher cross-validation classification accuracy than RHb. In an invasive animal study with nonhuman primates, we have also measured a superior covariation of oxygenation changes compared to deoxygenation, with intracortically recorded neural activity [2Hb, the SVM model generated using O2Hb was used to provide online feedback for known as well as open questions sessions. If the classification accuracies for at least three consecutive “training” sessions with questions with known answers were greater than the chance-level threshold, a new model was generated using the relative change in O2Hb across three training sessions to give online feedback. During an online feedback session, fNIRS data acquired online corresponding to each ISI was processed to obtain the relative change in O2Hb, as described above, across all the channels. The mean of the relative change in O2Hb across all the channels was used as test feature to map onto model space. Upon mapping of this test feature onto the model space, the SVM predicted  the side of the hyperplane the test feature fell on. Depending on the value of the predict label, appropriate feedback was provided to the patient: if the predict label was 0, the patient was given feedback that his or her answer was recognized as “no,” and if the predict label was 1, the patient was given feedback that his or her answer was recognized as “yes.”The bert law ,61 to caactivity  supportifNIRS provides three different signals: oxyhemoglobin (O2Hb), deoxyhemoglobin (RHb) and total hemoglobin (THb) [2Hb, only the results from the offline processing of O2Hb data will be shown along with the EEG and EOG data. The relative change in O2Hb, EEG, and EOG data were processed offline to determine:in (THb) ,61. As ma)2Hb, EEG, and EOG) during the ISI of true (yes) and false (no) sentences (in the time domain).The statistical difference in the particular physiological signal  across different channels in a session.To ascertain the difference between the averaged ISI of true and false sentences, b)2Hb, the EOG signal, and the EEG signal power spectrum during ISI corresponding to true and false sentences.The statistical difference in the offline classification accuracy of the relative change in Ot-test were used.For the EEG, frequencies between 0 and 30 Hz, estimated by Welch’s method , were usc)fNIRS SVM classification accuracy.The statistical difference of frequency bands’  features averaged daily-wise from EEG signals and their relationships with fNIRS classification accuracy was computed to find relevant relationships of low EEG rhythms with the BCI experimental procedure outcome. Details are provided in the Methods section of Frequency bands’ mean power and their “variability” were estimated using Welch’s method ,58. For The performance of the binary SVM classifier was ascertained by plotting the ROC curve. The ROC curve was created by plotting the TPR against the FPR (obtained from the contingency table created for each session) and the average of all the sessions, separately for each patient, using the four possible outcomes of a binary SVM classifier. The formation of contingency table for training and feedback sessions for each participant is described in the Receiver operating characteristic curve section of Semantic concordance rate (SCR) was calculated to ascertain the consistency and/or concordance of the answers between semantically equivalent but contrasting true and false sentences requiring “yes” and “no” answers, respectively. SCR  was calculated for all semantically related sentences presented to each patient. The method employed to calculate the semantic concordance rate is described in the Semantic concordance rate (SCR) section of S1 TREND Checklist(PDF)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.S1 TableSection A. Lists the daily-wise EEG frequency domain results of each patient. The number of days for each patient were: F, 14; G, 17; B, 12; and W, 6. Middle-frequency bands’ mean power and their “variability” were compared between sentence presentation interval and sentence’s ISI. See p-value. Section B. Enlist the averaged correlation between daily-wise EEG frequency bands’ mean power and fNIRS CA for each patient. The averaged correlation was computed across selected intervals  and across all electrodes. Column 4 lists the mean and standard deviation of each averaged correlation across intervals and electrodes with CA. Column 5 lists the p-values of the tested null hypothesis of whether the median of averaged correlation was zero. Further, the number of days of each patient was split in successful and unsuccessful days using the chance-level threshold. Then, the hypothesis of whether the particular band mean power distribution medians of successful and unsuccessful days differed was tested . The effect of this comparison  is reported in column 7. “Rest” stands for resting interval before sessions. “ISI” stands for interstimuli interval. “SP” stands for sentence presentation interval. “Succ.” and “Unsucc.” stand for successful and unsuccessful days, respectively. The symbol ≈ means that the band mean power medians of successful and unsuccessful days were similar. The symbol < means that the band mean power medians of successful and unsuccessful days differed significantly. The symbol * denotes a significant p-value. See fNIRS classification accuracy for details. S1 Table data is located at https://doi.org/10.5281/zenodo.191929.(XLSX)Click here for additional data file.S2 Tablehttps://doi.org/10.5281/zenodo.192128.S2 Table data is located at (XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Tablehttps://doi.org/10.5281/zenodo.192398.Contingency table formed using the average of all the training sessions. S4 Table data is located at (XLSX)Click here for additional data file.S5 Tablehttps://doi.org/10.5281/zenodo.192400.Contingency table formed using the average of all the feedback sessions. S5 Table data is located at (XLSX)Click here for additional data file.S6 Tablehttps://doi.org/10.5281/zenodo.192401.Contingency table formed using the average of all the training sessions. S6 Table data is located at (XLSX)Click here for additional data file.S7 Tablehttps://doi.org/10.5281/zenodo.192402.Contingency table formed using the average of all the feedback sessions. S7 Table data is located at (XLSX)Click here for additional data file.S8 Tablehttps://doi.org/10.5281/zenodo.192406.Contingency table formed using the average of all the training sessions. S8 Table data is located at (XLSX)Click here for additional data file.S9 Tablehttps://doi.org/10.5281/zenodo.192407.Contingency table formed using the average of all the feedback sessions. S9 Table data is located at (XLSX)Click here for additional data file.S10 Tablehttps://doi.org/10.5281/zenodo.192408.Contingency table formed using the average of all the training sessions. S10 Table data is located at (XLSX)Click here for additional data file.S11 Tablehttps://doi.org/10.5281/zenodo.192409.Contingency table formed using the average of all the feedback sessions. S11 Table data is located at (XLSX)Click here for additional data file.S12 Tablehttps://doi.org/10.5281/zenodo.191982.S12 Table data is located at (XLSX)Click here for additional data file.S1 FigA. Power spectrum density. Power spectrum density (PSD) of electroencephalographic (EEG) signal corresponding to YES (red solid trace) and NO (blue dashed trace) sentences’ ISI acquired from channel FC6 in patients F, G, B, and W. In each subplot, the x-axis is frequency in hertz and the y-axis is channel FC6 EEG in dB (μV2/Hz). S1A Fig data is located at https://doi.org/10.5281/zenodo.192386; https://doi.org/10.5281/zenodo.192388; https://doi.org/10.5281/zenodo.192390; https://doi.org/10.5281/zenodo.192391. B. Electrooculogram signal. The electrooculogram (EOG) signal corresponding to YES (red solid trace) and NO (blue dashed trace) sentences’ ISI in patients F, G, B, and W. In each subplot, the x-axis is time in seconds and the y-axis is EOG in micro volt (μV). S1B Fig data is located at https://doi.org/10.5281/zenodo.192386; https://doi.org/10.5281/zenodo.192388; https://doi.org/10.5281/zenodo.192390; https://doi.org/10.5281/zenodo.192391.(EPS)Click here for additional data file.S2 FigReceiver operating characteristic (ROC) curve of the binary support vector machine (SVM) classifier. (A) Training and (B) feedback sessions. Each circle in the ROC curve space represents false positive rate (FPR) versus true positive rate (TPR) for each session. Sessions with the same coordinate points in the ROC space are represented by concentric circles. The red star along with the coordinate points in the ROC space represent FPR versus TPR of all the sessions combined. In the figure panels A and B, the x-axis is the FPR and the y-axis is TPR. The thick diagonal line dividing the ROC space represents chance level. Points above the diagonal represent good classification results (better than random); points below the line represent poor classification results (worse than random). S2 Fig data is located at https://doi.org/10.5281/zenodo.192398; https://doi.org/10.5281/zenodo.192400.(EPS)Click here for additional data file.S3 FigReceiver operating characteristic (ROC) curve of the binary support vector machine (SVM) classifier. The description of this figure is the same as described in https://doi.org/10.5281/zenodo.192401; https://doi.org/10.5281/zenodo.192402.(EPS)Click here for additional data file.S4 FigReceiver operating characteristic (ROC) curve of the binary support vector machine (SVM) classifier. The description of this figure is the same as described in https://doi.org/10.5281/zenodo.192406; https://doi.org/10.5281/zenodo.192407.(EPS)Click here for additional data file.S5 FigReceiver operating characteristic (ROC) curve of the binary support vector machine (SVM) classifier. The description of this figure is the same as described in https://doi.org/10.5281/zenodo.192408; https://doi.org/10.5281/zenodo.192409.(EPS)Click here for additional data file.


Staphylococcus aureus (MSSA) isolates can indicate the emergence of novel sequence types (ST). The diffusion of MSSA ST can be tracked by combining established genotypic profiles with phenotypic surveillance data. ST398 emerged in New York City (NYC) and exhibits resistance to clindamycin and erythromycin but tetracycline susceptibility . Trends of potential ST398 were examined in a national cohort of all Veterans Health Administration patients with MSSA invasive infections during 2003–2014.Changing phenotypic profiles of methicillin-susceptible A retrospective cohort of all patients with MSSA invasive infections, defined as a positive clinical culture from a sterile site, during 2003–2014 was created. Only isolates tested against clindamycin, erythromycin and tetracycline were included. Annual hospital-level proportions of potential ST398 were compared according to facility distance from NYC and region.p < 0.01) reflect increases in potential ST398 over time in hospitals nearer to NYC.A total of 34,025 patient isolates from 136 VA medical centers met the inclusion criteria. Of those, 4582 (13.5%) met the definition of potential ST398. Potential ST398 increased over the 12-year cohort and diffused outwards from NYC. Incidence Rate Ratios of >1.0 (S. aureus infections.We observe an increase in the phenotypic profile of potential ST398 MSSA isolates in invasive infections in a national cohort of patients in the US. The increase is not evenly distributed across the US but appears to diffuse outwards from NYC. Novel MSSA strain emergence may have important clinical implications, particularly for the use of clindamycin for suspected  Staphylococcus aureus (SA), either methicillin-resistant (MRSA) or methicillin-sensitive (MSSA), has implications for the availability and efficacy of empiric therapy options. Detecting and tracking such an emergence is difficult, however, given the lack of nationwide genotyping databases. Isolates collected in routine clinical care are seldom genotyped and retained in an isolate bank for future analysis. As a result, analysis of phenotypic proxies for genotypes, based on susceptibility panels completed during routine clinical treatment, provide a method for hypothesis development regarding the emergence of novel strains. A change in SA susceptibility patterns would suggest changes in the underlying genotypic strains that are circulating and provide impetus for funding large-scale directed genotypic studies.The emergence of novel genotypes of When genotyping studies for SA have been completed, they have overwhelmingly focused on MRSA . Yet eveA newly emerging strain that has been detected both phenotypically and genotypically in the US is sequence type 398 (ST398). ST398 MRSA is of human origin but is more often reported in the literature as having an association with livestock exposure –18. ST39ST398 MSSA presents a case study for how phenotypic analysis can be used to document the potential diffusion over space and time of an emerging SA strain type. In systematic surveillance of NYC hospitals for MSSA ST398, Uhlemann et al. indicated that the majority of detected isolates shared a resistance profile: 100% (64/64) were tetracycline-susceptible and 97% (62/64) were clindamycin-resistant and erythromycin-resistant . In contpotential ST398, was present in and diffusing among veterans across the US. The emergence and diffusion of this novel MSSA phenotype, with resistance to frequently used antimicrobials, has important clinical implications for empiric therapy in US healthcare settings.The Veterans Health Administration (VHA) represents the only nationwide healthcare provider in the US, with standardized procedures for testing and reporting of antibiotic susceptibilities. This study makes use of this singular large national database to evaluate a possible emergent phenotypic profile over space and time. Using susceptibility profiles from patients with MSSA invasive clinical isolates, we sought to examine spatial and temporal trends in tetracycline-susceptible and clindamycin-resistant and erythromycin-resistant MSSA bacteria to determine whether this phenotype, which we designate as A retrospective cohort of all patients from VHA facilities in the contiguous US with MSSA invasive infections during 2003–2014 was created. An invasive infection was defined as a positive clinical culture from a sterile body site such as blood or synovial fluid; specimens from non-sterile sources such as urine, sputum and wounds were excluded. Only those MSSA isolates that were tested against all three classes of antibiotics  were included in the analysis. All microbiology laboratories within the VHA system are required to follow guidelines recommended by Clinical Laboratory Standards  . The numThis study used medical, microbiological, and demographic data extracted from the Veterans Affairs’ (VA) electronic health record for the VA’s Corporate Data Warehouse and accessed through the VA Informatics and Computing Infrastructure, as previously described . The insThe distance of each VAMC from NYC was calculated in kilometers using ArcMap 10.2  Fig. . FacilitA Poisson generalized estimating equation (GEE) regression model, with counts of potential ST398 in each VAMC in each two-year period as the outcome variable, explored the relationship between phenotypically potential ST398 and distance from NYC over time while accounting for repeat observations in hospitals over time. Because the majority of VAMCs had zero isolates matching the phenotypic profile in one or more years, an overdispersed model was fitted. Total invasive MSSA infections were included as an offset variable. Distance was included as a categorical variable, with hospitals grouped at <50 km from NYC and then in 1000 km increments. An interaction term between year and distance category was included in the model to detect regional variability in temporal trends, and incidence rate ratios (IRRs) for temporal trends for each distance category were calculated based on the model. Category-specific IRRs were also calculated for each distance category with hospitals >4000 km from NYC as the reference category to detect regional variability in baseline prevalence rates. Model diagnostics, including residual plots and dispersion measures, were examined to assess appropriateness of the model. Statistical analysis was completed in SAS version 9.4 .In 2003–2014, 47,513 patients from 136 VAMCs had sterile-site cultures positive for MSSA. Of these, 34,025 (72.2%) were tested against all three antibiotics. The number of sterile site MSSA isolates tested against all three antibiotics varied over time, rising from 62.2% in 2003 to 76.05% in 2014. Among the included sterile site MSSA isolates, 4582 (13.5%) exhibited clindamycin resistance and erythromycin resistance with tetracycline susceptibility and were potentially ST398. The proportion of isolates with this phenotypic profile increased over time, from a low of 5.7% in 2003 to a high of 16.1% in 2010, falling to 14.9% in 2014  in NYC VAMCs  and the area closely surrounding NYC (50-999 km)  when compared to those facilities furthest from NYC (Table p < 0.01).Results of the Poisson GEE regression indicated that, at the facility level, there was a significantly higher proportion of potential ST398 among MSSA isolates for hospitals in NYC  guidelines, such as for testing inducible clindamycin resistance, we do not have information on adherence in individual facilities. Finally, the VHA patient population, comprised of predominantly older white males, is not representative of the US population as a whole.We cannot definitively conclude the observed change in phenotypic profiles from 2003 to 2014 in the VHA MSSA cohort is due solely to ST398. However, there is circumstantial evidence that ST398 MSSA is emerging based on similarities to genotyped isolates in the literature and a similar association with distance from NYC, the putative epicenter of ST398 MSSA in the US. Within the VHA data, we document higher prevalence of isolates with a specific phenotypic profile in NYC hospitals in 2003–2004 with lower prevalence at greater distances from NYC. This pattern changed over the years of the study as overall potential ST398 increased in facilities further from NYC.In contrast to MRSA, seldom are nationally representative sets of MSSA isolates stored and genotyped. Until a nationwide data bank of isolates becomes available for genotypic evaluation, phenotypic surveillance of novel type emergence, followed by genotypic analysis in local healthcare settings, will have to suffice. Such phenotypically informed and directed genotypic analysis is more efficient and cost-effective than efforts to genotype all clinical isolates.Based upon a retrospective analysis of MSSA susceptibility data, our findings document the emergence and diffusion of a changing MSSA susceptibility pattern, suggestive of potential ST398, which occurred within the VHA system between 2003 and 2014. The diffusion of a novel MSSA genotype that is resistant to commonly-prescribed antimicrobials, and that is potentially more fit and transmissible than other genotypes, warrants attention as it can limit the options for empiric antimicrobial therapy in patients with suspected SA infections. Phenotypic profiles generated during routine clinical care can be used to evaluate hypotheses about changing genotypic patterns and to target isolates for detailed genotyping by standard methods such as spa typing, pulsed-field gel electrophoresis (PFGE) or even whole genome sequencing. Finally, these findings also suggest that establishing a nationwide surveillance system with banked isolates, regardless of their resistance to methicillin and other beta-lactams, could have significant epidemiologic and clinical utility.