PD-L1/JAK2/PD-L2 co-amplification using fluorescent in-situ hybridization assay (FISH). PD-L1 positivity  was present in 32/77 (42%) and 33/71 cases (46%) using SP142 and SP263 antibodies, respectively. Concordance between the two anti-PD-L1 clones was high with only three (4%) discrepant cases. The strongest and consistent (10/11 cases) expression was observed in cHL and primary mediastinal B-cell lymphomas (3/3). Diffuse large B-cell lymphomas (DLBCL) were frequently positive (13/26) irrespective of subtype. Follicular (1/8), peripheral T-cell (3/11) and mantle cell (1/8) lymphomas were rarely positive, while small lymphocytic lymphoma/CLL and marginal zone lymphomas were consistently negative (3/3). Co-amplification/CNVs of PD-L1/JAK2/PD-L2 were observed in 3 cases of DLBCL and cHL, respectively. Of note, all three cHL-amplified cases were positive by FISH, but not by NGS. Since only a fraction of the IHC positive lymphoma cases were positive by FISH and NGS assays, other mechanisms are involved in PD-L1 upregulation, especially in DLBCL. FISH assay may be more suitable than NGS assay for determination of PD-L1 alterations in cHL.Targeted immunotherapy based on PD-1/PD-L1 suppression has revolutionized the treatment of various solid tumors. A remarkable improvement has also been observed in the treatment of patients with refractory/relapsing classical Hodgkin lymphoma (cHL). We investigated PD-L1 status in a variety of treatment resistant lymphomas. Tumor samples from 78 patients with therapy resistant lymphomas were immunohistochemically (IHC) investigated for the expression of PD-L1 using two antibody clones . Thirteen PD-L1+ cases were further analyzed for gene copy number variations (CNV) by NGS and for  PDCD1 gene) and one of its two known ligands, the programmed death ligand-1  are among the therapeutically most important checkpoint proteins that mediate tumor-induced immune suppression through T-cell downregulation , after removing outliers. Underperforming regions were excluded to ensure that the reportable regions were created from high quality data. A region was considered amplified if the normalized region depth was greater than or equal to 6 copies above the background ploidy. In order for a gene to be called amplified, a predefined proportion (90%) of the regions within that gene should be called amplified. The final output file included gene-level calls and region-level calls for each case.Batch sequencing run QC includes Cluster Density (supported number of clusters created per mm2 in appropriate range ~150–300); Reads Passing filter (Number of reads included in the data production) >65%; Q30 score—99.9% of base calls are accurate . Also the batch controls  must pass and produce acceptable and expected results. From a sample to sample passing quality metric, each sample must have >400 average depth of coverage overall or the case is repeated or reported out as indeterminate.The χ2 test was used for comparisons of the variables and groups while the Spearman correlation rank was applied for the correlation between the variables. The differences were considered significant at a p-value <0.05. All data were analyzed using IBM SPSS v.19 .The study included samples from 78 patients  diagnosed with refractory and/or relapsed lymphomas of B- and T-cell lineages. The mean patient’s age was 55.6 years . Histotypes included 11 cases of cHL , 26 cases of DLBCL , 9 cases of mantle cell lymphomas, 8 cases of follicular [FL]; 4 cases of marginal zone lymphoma; three cases of primary mediastinal B-cell lymphoma and small lymphocytic/chronic lymphocytic leukemia [SLL/CLL], respectively; single cases of lymphomatoid granulomatosis [LG], mixed FL/DLBCL, and B-cell lymphoma (not specified). The study also included 11 peripheral T-cell lymphomas .Results of PD-L1 expression were available for 77 cases while 71 cases had interpretable results for both anti-PD-L1 clones  was 32/77 (42%) by SP142 and 33/72 (46%) by SP263 antibody . The higThe mean percentage of PD-L1 positivity in tumor cells was 21% . Seven out of 10 positive cHL (70%) had PD-L1 positivity in 100% of the neoplastic cells Figs  and 2B aWe also evaluated PD-L1 positivity in adjacent inflammatory (reactive) cell population; Fifty-five out of 58 cases (95%) had PD-L1 positivity in reactive/inflammatory cells  in comparison with NHL positive cases . We found an excellent concordance between SP142 and SP263 clones  with onlResults of NGS/FISH assays are summarized in PD-L1 and PD-L2 without JAK2 gene alterations while another DLBCL case had co-amplification of all three genes. Among the 8 negative cases, four cases were cHL. These cases were further tested by FISH and three of them (75%) exhibited co-amplification of PD-L1/JAK2/PD-L2 genes (PD-L1 gene) while the third case harbored ≥6 copies of PD-L1 per tumor cell. One of the positive DLBCL cases was also confirmed by FISH while another, non-amplified DLBCL case by NGS exhibited no 9p24.1 alterations by FISH.Six out of 13 tested cases (46%) were positive by NGS or FISH . Two out of 10 tested cases by NGS exhibited co-amplification at 9p24.1: One case (DLBCL) harbored co-amplification of L2 genes ; two casImmune check point blockade with PD-1/PD-L1 has dramatically changed the cancer treatment paradigm with impressive results in several solid tumors as well as in cHL. PD-L1 overexpression has also been described in cancer subtypes beyond those that have been so far considered for immune check point inhibitors , 24–26, Patients with relapsed/progressive malignant lymphomas have limited therapeutic modalities and new therapeutic approaches are of crucial importance. Our study revealed over-expression of PD-L1 in cHL, DLBCL , a subset of peripheral T-cell lymphomas and a single case lymphomatoid granulomatosis. These findings are consistent with comprehensive surveys of Menter et al. [clones E1L3N  and SP142   and ChenPD-L1 gene [JAK2 (Janus kinase 2) gene involved in JAK2-STAT signaling that further may activate PD-L1 [PD-L2 gene, which is another ligand of PD-1. Similar to previous data, we showed that a subset of PD-L1+ lymphomas (both cHL and non-Hodgkin lymphoma) may harbor genetic alterations at 9p24.1 amplicon, which implies that the remaining non-amplified cases may have “adaptive” PD-L1 overexpression without underlying PD-L1 gene alterations [PD-L1 and PD-L2 without JAK2 gene alterations, which is in line with a recent study of Budczies et al. [PD-L1 copy number variations  across different cancer subtypes with direct impact on its protein and mRNA expression. In particular, cHL are characterized by consistent PD-L1/PD-L2 gene alterations [PD-L1 gene alterations in cHL. FISH method appears to be a more suitable methodology than NGS for assessing 9p24 status in tumors with a low cancer cell density as it allows for morphologic  identification of single amplified RS cells within heterogeneous (reactive) cell populations in cHL.There is increasing number of studies indicating that alterations at 9p24.1 affect PD-1 ligands (“9p24.1 amplicon”), particularly -L1 gene . This amte PD-L1  and PD-Lerations . One cass et al. . The auterations . One of PD-L1, PD-L1 and JAK2 genes. FISH assay may be more suitable than NGS assay for determination of PD-L1 alterations in cHL.We conclude that a substantial proportion of relapsed/refractory B-cell and T-cell non-Hodgkin lymphomas and nearly all classic Hodgkin lymphomas overexpress PD-L1 protein, implying a potential utility of checkpoint blockade therapy in these difficult to treat diseases. Anti-PD-L1 clones SP142 and SP263 exhibit an excellent concordance and both antibodies may be used for IHC detection of PD-L1 in tumors. We also confirm that a subset of refractory, PD-L1 positive lymphomas may harbor genetic alterations of 9p21.4 amplicon affecting S1 File(XLSX)Click here for additional data file.


Dystroglycan (DG) is an adhesion receptor complex composed of two non-covalently associated subunits, transcribed from a single gene. The extracellular α-DG is highly and heterogeneously glycosylated and binds with high affinity to laminins, and the transmembrane β-DG binds intracellular dystrophin. Multiple cellular functions have been proposed for DG, notwithstanding that its role in skeletal muscle appears central as demonstrated by both primary and secondary severe muscular dystrophic phenotypes collectively known as dystroglycanopathies. We recently analysed the molecular phylogeny of the DG core protein and identified the α/β interface, transmembrane and cytoplasmic domains of β-DG as the most conserved region. It was also identified that the IG2_MAT_NU region has been independently duplicated in multiple lineages.To understand the evolution of dystroglycan in more depth, we investigated dystroglycan gene structure in 35 species representative of the phyla in which dystroglycan has been identified . The gene structure of three exons and two introns is remarkably conserved. However, additional lineage-specific introns were identified, which interrupt the coding sequence at distinct points, were identified in multiple metazoan groups, most prominently in ecdysozoans.A coding DNA sequence (CDS) intron that interrupts the encoding of the IG1 domain is universally conserved and this intron is longer in gnathostomes (jawed vertebrates) than in other metazoans. Lineage-specific gain of additional introns has occurred notably in ecdysozoans, where multiple introns interrupt the large 3′ exon. More limited intron gain has also occurred in placozoa, cnidarians, urochordates and the DG paralogues of lamprey and teleost fish.The online version of this article (doi:10.1186/s13104-016-2322-x) contains supplementary material, which is available to authorized users. Drosophila melanogaster and Caenorhabditis elegans. It forms a bridging element that connects the internal cytoskeleton to basement membrane extracellular matrix [Dystroglycan (DG) is an adhesion receptor complex that provides mechanical stability to a wide variety of cells and tissues in mammals, zebrafish, r matrix . In thisr matrix . β-DG spr matrix .DG has been related to the function of skeletal muscle since its initial identification in rabbit sarcolemma . The calLeishmania mexicana (PDB:2C34) (Z-score of 5.1 and an RMSD of 3.2 Å over 82 residues) [The two subunits of DG are transcribed from a single gene. The domain organization of the primary protein product is as follows: a signal peptide; immunoglobulin-like domain 1 (IG1); S6 domain  .Fig. 1Arcis) of carbohydrate moieties that protrude from the neighbouring mucin-like region, and therefore could have additional functions within the glycosylation and maturation pathway of the dystroglycan precursor molecule [For the maturation of α-DG, the N-terminal region (IG1 and S6 domains) is considered highly important. Indeed, the N-terminal region in isolation displays a residual laminin-binding activity  and is lmolecule .Mnemiopsis leidyi and Pleurobrachia bachei [Nematostella vectensis (6X).Recently, we conducted the first extensive evolutionary study of the dystroglycan core protein and demonstrated a high degree of conservation in all metazoan phyla except ctenophores, where DG is absent from the two available species, a bachei . Our stua bachei . A majorDrosophila melanogaster [Apart from information on the DG gene in a few mammalian species , 23 or onogaster , no detanogaster . EspeciaExaiptasia pallida  intron (mini-intron) that interrupts the encoding of the S6 domain of α-DG  also has two DG genes, each with similar gene structure to the Dag1 genes of bony fish  four additional introns  split the CDS  and in species representative of other arthropod classes (Crustacea and Chelicerata) (Table C. elegans (nematode) includes multiple introns that interrupt the region encoding the IG2 domain and the cytoplasmic domain, respectively  interrupt the N-terminal encoding sequences in a position similar to the additional introns in the DG gene of B. floridae  in which six repetitions of IG2_MAT_NU are present [In our prior study of the molecular phylogeny of DG protein, we identified that the region including the IG2_MAT_NU domains has been independently duplicated in a number of phyla . This phenomenon is particularly striking in the DG of the sea anemone  present . The curA. queenslandica (Porifera) and 48 bp in Capitella teleta (Annelida) and yet comprises up to ~30 kb in Ornithorhynchus anatinus and other mammals , in C. teleta (annelid) and in T. castaneum (insect)  introns. These two introns are located within the 5′ portion of the gene, making the 3′ region essentially intron-less , arthropods (in particular Drosophila melanogaster) and nematodes  includes multiple introns. Larger genomes generally contain genes with longer introns [In vertebrates, a striking characteristic of  introns  and inde introns . A tende introns , 34. The introns . Interes introns . However introns .We found that the observed repetitions of the intronless IG2_MAT_NU module in some species  do not iThe biological significance of the IG1 domain for DG function has been underscored by the recent identification of two novel compound heterozygous DG missense mutations, V74I and D111N, that are associated in a patient with asymptomatic hyperCKemia and hypoglycosylation of α-dystroglycan . The mutD. melanogaster DG (miR9a (CCAAAGA) in myotendinous junction and miR310 s (UGCAAUA) in the brain) [Homo sapiens , Mus musculus  and Hydra magnipapillata . This conservation might indicate that some of the regulatory mechanisms observed in Drosophila melanogaster might also be relevant to other species.Further work will be needed to analyse the 5′ and 3′ untranslated regions (UTR) of dystroglycan genes for possible conserved transcription factor binding sites and/or other regulatory elements such as miRNA hybridization sites , 40. A pe brain) , 42 are Pleurobrachia bachei and Mnemiopsis leidyi), and phylum Ctenophora is not included in the model. Our previous study of the molecular phylogeny of the DG protein demonstrated that the IG2_MAT_NU region and the domains of β-dystroglycan are the most highly conserved regions that might reflect the ancestral form of DG [A. queenslandica DG indicates that the IG1 domain and IG1-intron have been part of the DG gene from its earliest origin. In contrast, the S6 domain appears to have been gained in the last common ancestor of placozoans, cnidarians and bilaterians, perhaps by exon shuffling . Searches were completed as of the end of January 2016. Searches with protein sequences were performed by BLASTP at NCBI Genbank at default parameters and were based on the protein sequences studied in [All the gene sequences investigated were retrieved either from the Ensembl database  or from udied in . Dystrogudied in .http://www.ebi.ac.uk/Tools/msa) and are presented in BoxShade 3.21 (http://www.ch.embnet.org/software/BOX_form.html). Secondary structure elements are reproduced from PDB 1U2C [Multiple sequence alignments of nucleotide or protein sequences were constructed in MUSCLE 3.8  via the PDB 1U2C .Graph presentations and fitted lines were generated using KaleidaGraph (Synergy Software).


The detection of faked identities is a major problem in security. Current memory-detection techniques cannot be used as they require prior knowledge of the respondent’s true identity. Here, we report a novel technique for detecting faked identities based on the use of unexpected questions that may be used to check the respondent identity without any prior autobiographical information. While truth-tellers respond automatically to unexpected questions, liars have to “build” and verify their responses. This lack of automaticity is reflected in the mouse movements used to record the responses as well as in the number of errors. Responses to unexpected questions are compared to responses to expected and control questions . Parameters that encode mouse movement were analyzed using machine learning classifiers and the results indicate that the mouse trajectories and errors on unexpected questions efficiently distinguish liars from truth-tellers. Furthermore, we showed that liars may be identified also when they are responding truthfully. Unexpected questions combined with the analysis of mouse movement may efficiently spot participants with faked identities without the need for any prior information on the examinee. The use of faked identities is a very common issue. People can fake their personal information for a number of reasons. Faked autobiographical information is, for example, observed in sports, with players claiming to be younger than what they really are . Social From the beginning, starting with the pioneer work of Benussi , the ideThe Odyssey, told Polypheme that his real name was “No-man.” This lie was intended to fool Polypheme but was also supposed to be easily spotted as a lie by Polypheme’s one-eyed companions.By contrast, it could be very high when fabricating complex lies, such as when Ulysses, the hero of RT-based memory detection has a number of advantages over alternative psychophysiological techniques, especially when a high number of subjects are under scrutiny. First, RTs are less sensitive to strong individual or environmental changes, such as in the case of physiological parameters. Secondly, this technique has the unparalleled feature that it may be applied using merely a computer and administered to a large number of examinees over the Web. Currently, two memory-detection techniques based on RTs that are used to present words or sentences may be adapted as tools for identity verification. The Concealed Information Test (CIT-RT)  and the The CIT-RT is a technique that consists of presenting the critical information within a series of very similar, noncritical sources of distractor information. For example, if the concealed knowledge about a murder weapon is under scrutiny, a knife (the known murder weapon) will be presented together with distractors that are also potential murder weapons . For the innocent subjects, the response is expected to be similar to all stimuli. By contrast, for the guilty subject (with guilty knowledge for the weapon), longer responses for the critical item are expected . When applied to verify whether the autobiographical information that the examinee claims corresponds to the true identity, the CIT efficiently succeeds in distinguishing the identities of liars and truth-tellers .I am in front of a computer”) or certainly false  for the respondent and related to the moment of testing. The other two categories are represented by alternative versions of the autobiographical memory under investigation , with only one of the two being true. During the test, the examined subject performs a categorization task. The true autobiographical event is identified because it determines faster RTs when sharing the same motor response with certainly true sentences [The aIAT is a memory-detection methodology that exploits consistency/inconsistency between sentences. It includes stimuli belonging to four categories: two of them are logical categories represented by sentences that are certainly true . Available techniques cannot be used when the critical information that is evaluated for veracity  is not available.Here, we will present a new paradigm that overcomes the caveats of the available methods and may be used to identify whether personal information is true. Most importantly, we will show that a faked identity can be spotted in the absence of any information about the suspect’s true identity. Faked identities will be detected using unexpected questions combined with an analysis of mouse movements during the response in a binary classification task. We will show that the analysis of mouse dynamics efficiently detects whether the personal information that the examinee claims is true. In the experiments presented here, the participants do not respond by pressing YES/NO buttons using the keyboard, as in the RT-CIT or aIAT, but they are instead required to respond by clicking with a mouse virtual buttons appearing on the computer screen along with questions regarding their identities. The use of a mouse for recording responses has a number of advantages over the use of a keyboard. While the press of a button may permit only RTs to be recorded, mouse recording allows several indicators to be collected, including but not limited to RT . The technique is also promising regarding resistance to countermeasures, as a high number of movement parameters seems, in principle, more difficult to control entirely via efficient, planned countermeasures to lie detection.It has been shown that the analysis of mouse trajectories can capture cognitive complexity in stimulus processing when participants are required to deliver multiple-choice responses. This procedure has been applied to a large number of fields and has proved useful in highlighting cognitive complexity related to negative sentence verification , racial Here, we will present the results of an experiment in which the trajectories of motor responses using the mouse were investigated while the participants were tested on questions regarding their identities. Two types of questions were asked: expected questions and unexpected questions . Vrij anThe experiment reported here consists of a binary classification task involving expected and unexpected questions about identity. Expected questions covered typical information as reported in documents, while unexpected questions covered information that was well known and automatically retrieved by the truth-teller but that should be “computed-on-the-spot” by liars. An example of an expected question would be one’s date of birth, and a corresponding unexpected question would be the zodiac corresponding to the date of birth. While truth-tellers easily verify questions involving the zodiac, liars do not have the zodiac immediately available, and they have to compute it for a correct verification. The uncertainty in responding to unexpected questions may lead to errors. Furthermore, we found that the trajectory mouse response, analyzed using kinematic parameters and other spatial and temporal parameters intended to capture the uncertainty in motor response, could be useful in detecting deception. Deception, therefore, is expected to reflect itself in the form of the trajectories.In an identity verification task, the liars are typically required to learn the autobiographical information of a new identity and to take the test responding as if that information were real for them. For example, Verschuere et al.  asked su“Unexpected questions will increase a liar’s cognitive load” [For a truthful responder, unexpected questions are supposed to elicit the correct response automatically. By contrast, an identity liar has to reconstruct the non-rehearsed unexpected information and verify it. Therefore, this process takes time before the response is emitted, which is reflected in longer RTs. In short, ve load”  and thisIn the following, we will describe in detail the experiment structure and the measures collected. The ethics committee for psychological research of the University of Padova approved the experimental procedure.Forty Italian-speaking participants were recruited at the Department of Psychology of Padova University. The sample consisted of 17 males and 23 females. Their average age was 25 years (SD = 4.6), and their average education level was 17 years (SD = 1.8). All of the participants were right handed. These first 40 participants were used to develop the model that was later tested, for generalization, in a fresh new group of 20 Italian-speaking participants (10 liars and 10 truth-tellers). This second sample consisted of 9 males and 11 females. Their average age was 23 years (SD = 1.5), and their average education level was 17 years (SD = 0.83). Both groups of subjects provided informed consent before the experiment.Thirty-two sentences displayed in the upper part of the computer screen were presented to all of the participants. The squares representing the YES and NO responses were located in the upper left and upper right of the computer screen. Sixteen sentences required a YES response, and 16 required a NO response, for both the liars and the truth-tellers. The 32 experimental questions were preceded by 6 training questions (3 requiring a YES response and 3 requiring a NO response) on issues related to the identity not included in the experiment proper . Sentences that required a YES response belonged to the following categories:Expected questions: These included information that was rehearsed before the experiment, both for the truth-tellers and for the liars. The liars responded with personal information about fake identity profiles that the experimenter had assigned to them. The truth-tellers responded to questions regarding their true identities.Unexpected questions: The unexpected questions included information closely related to the false identities but not explicitly rehearsed before the experiment by either the truth-tellers or the liars. In this case, the liars responded to information related to the fake identities assigned to them, while the truth-tellers responded to the questions regarding their true identities.n = 8; 4 requiring a YES response and 4 a NO response) included personal information to which the subjects had to respond truthfully because they could not be hidden to the examiner supervising the test. For example, “Are you male?”  required a YES response, whereas “Are you a female?”  required a NO response. Therefore, the control questions required truthful responses by both the liars and truth-tellers, even if they were related to identity.Control questions: Control questions were intermixed with the expected and unexpected questions. The control questions (n = 16) required YES responses. By contrast, 16 questions derived from the expected, unexpected, and control questions required NO responses as displayed in For both the liars and the truth-tellers, half of the expected, unexpected, and control questions : the time between the appearance of the question and the beginning of the mouse movementReaction time (RT): the time between the appearance of the question and the virtual button-pressing performed with the mouseMaximum deviation (MD): the maximum perpendicular distance between the actual trajectory and the ideal trajectory (the line connecting the starting button with the expected response button)Area under the curve (AUC): the geometric area included between the actual trajectory and the ideal trajectoryMaximum deviation time (MD-time): the time taken to reach the point of maximum deviation from the ideal trajectoryx-flip: The total number of changes in directions of the mouse during the full trajectory on x-axisy-flip: The total number of changes in directions of the mouse during the full trajectory on y-axisn, Yn): the position of the mouse along the axis over timeX, Y coordinates over time , Reaction Time (RT), Maximum Deviation (MD), Area Under the Curve (AUC), Maximum Deviation time (MD-time), x-flip, y-flip, Y30, Y29, Y18, Y30–Y29, and Y29–Y18. For each of the variables we computed the average value of the 32 responses for each participant.pb = 0.68), AUC (rpb = 0.53), MD-time (rpb = 0.45), and Y29 (rpb = 0.42) .A correlation analysis was conducted to highlight the independent variables that had the maximum correlation with the dependent variable (truth-tellers vs. liars) and minimum correlation across the independent variables . We consIn this section, the steps followed to analyze the data and the procedure used in developing the ML classifiers are reported.Data and instructions to replicate the results are available as Supporting Information see  Text.The first analysis compared the responses of liars and truth-tellers by averaging across individual responses to both YES and NO responses. In Here we report examples of individual mouse trajectories in response to control questions and unexpected questions collected from a prototypical truth-teller  and a prTrajectories refer to responses to single questions. Note that this liar is responding truthfully to control questions. Nonetheless, his response diverges from the direct trajectory that ideally characterizes a truthful response see . This geWe analyzed the subjects’ performances separately for control, expected, and unexpected questions. In t-tests on the whole sample were carried out in order to compare left and right responses. We did not find any statistically significant difference both for MD-time  and Y29 . For AUC, we obtained the following results: t = -2.09 and p = 0.04, but the Cohen’s d value showed a small effect size (d = -0.33), and the Bayes Factor approached (BF = 1.2). In We investigated whether there is a difference in the trajectory and in response time between the questions to which subjects responded by moving a mouse to the right (questions requiring a NO response) and questions to which subjects responded moving a mouse to the left (questions requiring a YES response). The t-test, Cohen’s d and Bayes Factor.Feature selection isolated, from an original set of 13 predictors, 4 independent variables: errors, AUC, MD-time, and Y29. These were highly correlated with the group (truth-teller/liar). The following table see  reports Several machine learning (ML) classifiers were tested using a 10-fold cross-validation procedure as implemented by WEKA . We seleAs reported in After the development of the ML classifiers described above, a further sample of 20 participants (10 liars and 10 truth-tellers) was collected and tested using the models previously developed based on the original 40 participants. This group of participants was a totally new group that had never been used before for the analysis or model building. This procedure is regarded as an optimal strategy to avoid overfitting . The clTo better understand the contribution of control, expected, and unexpected questions in the classification we ran three separate models for each type of question. Results indicate that the major contribution derives from unexpected questions see . ClassifWe also investigated the relative weight of the predictors by eliminating the independent variables one by one and rerunning the classifiers. The results indicated that after eliminating the errors from the predictors, the classification accuracy dropped to around 75% for the cross-validation and around 70% for the test procedure . The major contribution in prediction accuracy comes from revealing errors to unexpected questions with mouse dynamic features fine tuning an already good classification. This is clear if we consider that predictions based solely on errors yielded the following results: Random Forest: cross-validation = 77.5%, test = 100%; Logistic: cross-validation = 82.5%, test = 100%; SVM: cross-validation = 80%, test = 95%; LMT: cross-validation = 85%; Test = 100%. After dropping AUC from the predictors, the classification accuracy remained stable in the test set and fell to 90% during cross-validation . Similar results were obtained when removing MD-time from the predictors . Finally, after discharging Y29 from the predictors, the accuracy both in the training and the test sets decreased slightly .th time frame.Briefly, the relative importance of the independent variables indicated that the total number of errors gave the major contribution in correctly distinguishing liars from truth-tellers, followed by the MD-time, the AUC, and the position of the mouse along the y-axis on the 29The errors to control and expected questions are virtually absent in truth-tellers see . Liars at = - 4.59, p<0.01; Cohen’s d = 1.60; BF = 16.42.Liars and truth-tellers make no errors to control questions and only a total 2/240 to expected questions. The difference between the two groups arises from unexpected questions with truth-tellers making a total 5/240 errors and liars 82/240. This indicates that for every error made by a truth-teller to unexpected questions liars make 16 errors. It is worth noting that liars make more errors to unexpected YES (60/120 where they lie) rather than unexpected NO (22/120 where they respond truthfully), n = 40 and German n = 20) with results for liars of t = -1.4, p = 0.17  and results for truth-tellers of t = 0.66, p = 0.52 .To check whether the model can efficiently classify participants from different cultures, we tested 20 German subjects (10 liars and 10 truth-tellers) with good results. To address the effects of culture on the generalization of results, we tested a sample of 20 participants native speakers of German in Düsseldorf  with questions in German. Participants provided informed consent before the experiment. Results from this group were evaluated using the model originally trained on the 40 Italian participants. The classification accuracy was the following: Random Forest = 95%, Logistic = 100%, SVM = 90%, LMT = 95%. Errors analysis see  indicateThe experimental design described in the manuscript requires that liars lie only when responding YES to expected and unexpected YES questions. In all of the other conditions , the liars responded truthfully see . An inteIn order to evaluate whether the trajectories of the liars also differed from those of the truth-tellers when they were not lying, we compared the two experimental groups on the independent variables previously used in developing the classifiers. The results of the independent t-test, reported in Both statistical analysis and ML analysis have shown that the markers of lying extended to questions to which they responded truthfully. Even when responding truthfully, the liars could be identified, but with lower accuracy. From a cognitive point of view, what is interesting here is that, in the experimental design, the mind-set of the liars also extended its effects to questions when they were responding truthfully. To our knowledge, this pattern of results has never been reported before and could be an indication of the level of sensitivity of the technique of mouse-movement analysis.To our knowledge, no techniques can accurately spot whether a subject’s ID is true or false without any information about the respondent’s true identity. In this paper, we report results on a new memory detection technique aimed at classifying whether an ID is true or faked when liars do not provide any personal information that is then included in the test itself.The participants responded using a mouse to questions regarding ID that required a YES/NO response. Mouse dynamics provide a rich source of data, as compared to similar binary classification tasks based on response buttons. While the data collected through button presses are limited to recording latency between the question onset and the button press, mouse response permits several parameters to be collected, including reaction times but also initiation time, velocity, acceleration, and the mouse’s trajectory.In order to develop a model that efficiently spots participants with faked identities, we tested the responders with questions that were expected and that liars over-learned in a preliminary learning phase . Together with expected questions targeting the ID document information, a set of unexpected questions related to the expected questions was also presented. Consider, for example, the place of birth. Expected questions that would appear on the ID card would be “Were you born in Pisa?” (requiring a YES response) or “Were you born in New York?” (requiring a NO response). Corresponding unexpected questions would be: “Is Florence the capital of your region of birth?”  and “Is Venice the capital of your region of birth?” . Another unexpected question related to the date of birth (derived from the date) was about zodiac. Truth-tellers are supposed to be able to retrieve the responses about their true zodiac more automatically than liars; therefore, their response is expected to be more rapid, with less errors, and characterized by a more direct mouse trajectory. In general, unexpected questions are supposed to be rapidly retrieved by truth-tellers while liars have to mentally “compute” the response from the original expected information .The research reported here demonstrated that mouse dynamics analyzed using a ML model yielded a correct classification of liars and truth-tellers with more than 90% accuracy. This result was achieved by developing a set of classifiers with comparable performance in the accuracy range 90–95% . Another group was collected and tested (10 truth tellers and 10 liars) to validate the model’s generalization. In this group, the accuracy was confirmed to be comparable to that of the group used for developing the classifiers (95% = 19/20 participants correctly classified), showing that the high accuracy achieved in the model-building stage was not the result of overfitting.Game theory is also a promising technique in deep learning. We did not evaluate whether more complex deep learning models based on game theory concepts –37 couldth time frame.We conducted an analysis to identify the most important predictor, which was total errors followed by the MD-time, the AUC, and the position of the mouse along the y-axis on the 29From a cognitive point of view, it is confirmed that unexpected questions may be used to uncover deception. The power of unexpected questions has been extensively examined in investigative interrogations . Here, wIt is interesting to note that our experimental design requires liars to respond truthfully to a number of questions. The analysis performed on such truthful responses indicates that liars are still detectable, even if with a lower accuracy, when they are not lying. Rosenfeld et al. showed that truth telling liars could be identified using P300, similarly to what we report here . It is iUnexpected questions require answers to be carefully crafted and this may be a limitation in online automatic usage of the technique. Further limitations of the present study include the fact that the procedure has been tested on participants of a single culture and generalization tested on participants belonging to a not so different culture (Germany). A further limit of the present research comes from the fact that the issue of faked ID detection does not permit a direct comparison with more validated lie detection techniques . Any comparison between techniques is therefore only indirect.With all these limitations in mind, we think that the use of unexpected questions combined with the analysis of mouse dynamics seems to be a promising avenue for uncovering deceptive responses.S1 Text(PDF)Click here for additional data file.S2 Text(PDF)Click here for additional data file.S1 Dataset(ZIP)Click here for additional data file.S2 Dataset(ZIP)Click here for additional data file.


The improvements brought by the integration of graphene onto silicon photonic waveguides could bring us a step closer to realising compact all-optical control on a single chip.The hallmark of silicon photonics is in its low loss at the telecommunications wavelength, economic advantages and compatibility with CMOS design and fabrication processes. These advantages are however impeded by its relatively low Kerr coefficient that constrains the power and size scaling of nonlinear all-optical silicon photonic devices. Graphene, with its unprecedented high Kerr coefficient and uniquely thin-film structure, makes a good nonlinear material to be easily integrated onto all-optical silicon photonic waveguide devices. We study the design of all-optical graphene-on-silicon (GOS) waveguide modulators, and find the optimized performance of MW cm This is due to limits of metallic interconnects facing signal attenuation and large power consumption at higher data rates2. One of the solutions is to replace them with optical interconnects. The replacement candidate, silicon photonics, is viable given its potential low cost and high compatibility with CMOS design and manufacturing process3. Silicon photonics also interface well with electronic transistors through power-efficient optoelectronic transceivers. Recently, Sun et al. has successfully demonstrated a working prototype of a chip-scale electronic-photonic system based on the silicon photonics platform4.The thriving success of the electronics microprocessor over the past four decades is achieved with the abundant availability of silicon. However, in recent years, the increasing demand for faster processing speed and larger bandwidth have not been met, saturating at around 3 to 4 GHz5. In all-optical computing for silicon photonics, the nonlinear effects are used to achieve modulation. Nonlinear effects in silicon photonics have been demonstrated to process optical signals at speeds of beyond 100 Gbit/s6. Besides processing optical signals, nonlinear effects are also used for sensing and generation of photons for lasing and amplification. However, the inherent nonlinear Kerr effects of silicon is of the low range of 6 × 10−18 m2 W−1. To achieve a reasonable level of contrast needed for optical modulation, nonlinear optical devices often need to be operated at high optical intensities and long optical device lengths. This results in high power consumption and large device footprints, which runs in contrary to the original aim to scale down device size and energy consumption in computing chips7.Current research is also pushing for elimination of electronic transistors for seamless integration of an all-optical computing platform−7 to 10−13 m2 W−1 15. Being a two-dimensional atomically thin-film material, graphene alone is not suitable to be used as photonic waveguide due to its poor optical confinement. There are efforts to design around the thin-film nature of graphene by implementing the nonlinear optical devices on graphene plasmonic waveguides21; however, due to their short propagation length of only a few micrometers23, they are not compatible with the longer-ranged photonics, only suitable to be used in an all-plasmonics platform.The best way to mitigate the disadvantages of silicon nonlinear photonics is to integrate them with novel high Kerr-coefficient materials while keeping the silicon platform for its economic advantages. One of the best candidate material is graphene, which has a high Kerr-coefficient from 1024, with a conclusion that graphene’s nonlinear performance is ordinary due to its high losses. However, in this paper, we show that if we take into account the nonlinear reduction in losses, or even designing extinction modulators, the performance of graphene may exceed that of silicon-on-insulator (SOI) waveguides.Prior papers discussed graphene-based modulators placed on dielectrics only in the context of its real refractive index changesHence, by integrating graphene onto silicon waveguides, we simultaneously make use of the photonic confinement and long-range waveguiding properties of silicon-based waveguides while leveraging the high optical nonlinearities of graphene for optical switching. In this paper, we will study in detail how to integrate graphene onto a silicon waveguide and the corresponding performance improvements in all-optical switching on silicon photonic waveguides.2 with refractive index of 1.44. A graphene sheet with atomic thickness of ~0.3 nm is then laid on top of the waveguide, with a sheet width large enough to cover the fundamental mode-area of the silicon rib. Our choice of adopting the SOI rib waveguide is based on extensive studies on its good confinement and low waveguide propagation and bending losses26. On top of that, this structure exposes the top waveguide surface, which allows easy placement of graphene close to the mode-propagation area, allowing graphene to have maximum interaction with the fundamental optical mode. To control nonlinear optical response of the modulator, an optical pump is shined directly on the graphene surface to modulate the Kerr refractive index.Figure Ageff, which is written asTo quantify the interaction of the waveguide mode with the graphene sheet, we define the effective mode area of graphene, Ageff are easily found with the help of mode simulations in COMSOL. Here, we shall limit our study to only the fundamental TE and TM modes of the silicon rib waveguide. Figure Ageff of the TE and TM modes vary with wavelength in the range from 1.3 to 1.7 µm. The Ageff of the TE mode is relatively constant at around 1.2 × 103 µm2. On the other hand, the Ageff of the TM mode rises significantly with the increase in wavelength. A closer inspection on the electric-fields on the TM mode reveals their asymmetrical distribution at the top and bottom interfaces of the waveguide. At longer wavelengths, the electric-fields are increasingly distributed more to the bottom of the waveguide, thus the mode interacts less with the graphene sheet.Solutions of 27ω, relaxation frequencies ν1 and ν228, and Fermi-level EF at room temperature T = 300 K. The optical conductivity can be used to derive the refractive index of graphene usingdeff is the graphene’s layer thickness approximated to 0.3 nm. The refractive index of graphene is plotted with wavelength in Fig. EF < 0.4 eV), graphene is a lossy dielectric in the wavelength range from 1.3–1.7 µm. Graphene-on-substrate has a natural substrate doping of around 0.1–0.2 eV, thus we will base our device analysis around this range of Fermi levels29.The linear graphene optical conductivity is described by the Kubo formula−11–10−13 m2W−1 around 1.55 µm15. Graphene’s nonlinear conductivity is calculated using semiconductor Bloch equations based on graphene’s tight-binding model by Cheng et al.15. These values can be transformed to the nonlinear refractive index using30ngraphene and kgraphene are the real and imaginary linear refractive indices of graphene, and EF as shown in Fig. EF from 0.1–0.25 eV, much unlike the behavior in the midinfrared where the low EF regime has nonlinearities higher by a few orders21.This can be qualitative explained by the fact that at low-frequency regime the optical response is dominantly contributed by intraband process which has a stronger Fermi level and frequency dependence while at high-frequency regime the dominating interband process has a much weaker frequency and Fermi level dependences13. At 1.55 µm, the Kerr coefficient of graphene is between 2–5 × 10−11 m2W−1, which is seven orders higher than silicon’s Kerr coefficient of 6 × 10−18 m2 W−1.Meanwhile, the nonlinear optical conductivity of graphene has been obtained from theory and experiments, which ranges from 1028, is to lower the overall propagation loss of graphene after modulation. This would augment the phase-modulation performance of the graphene-on-silicon waveguide, and at the same time enable the design of an extinction-based modulator.It is noted that the magnitude of graphene’s real and imaginary Kerr coefficients is negative. The impact of the negative imaginary Kerr coefficient, also called the saturable lossFinally, we also take into account the saturation intensity of the nonlinear Kerr modulation using the standard experimental definition−2 as shown in Fig. The saturation intensities are in the range of a few MW cmΔn and Δk, would give us the effective nonlinear refractive index throughTo obtain the effective nonlinear modulation of the GOS waveguide would require analysis of the entire optical mode propagation in the waveguide structure. This is easily achieved through mode simulations in COMSOL, where the effective refractive indices before and after the optical modulation are analysed. In order to give a more accurate picture of the nonlinear performance contributed by graphene, we have omitted the nonlinear refractive index of silicon from our simulations. The difference between the values, n and k denote the effective waveguide indices instead of the material indices. Also, the optical intensity, I, has the implicit term of n2 and k2 values, we use I = 1 kW cm−2 in the simulation, which is significantly less than Isat.Here, it is noted that n2 and k2 for both the fundamental TE and TM modes. The slight increase of the waveguide nonlinear indices with wavelength for the TE mode is in line with trend for the nonlinear material indices for graphene. For the TM mode, however, the waveguide nonlinear indices drop off at the longer wavelengths due to diminished optical interaction with graphene, which arose from the asymmetric distribution of the electric-fields as has been shown before in Fig. The linear effective waveguide indices of the GOS waveguide are shown in Fig. k2 is at least an order higher than that of n2, even though the material n2 and k2 magnitudes are almost the same. This is intuitively understood by looking at the linear material properties of both silicon and graphene. The refractive index of silicon is large (nSi = 3.48) and since the optical mode occupies the silicon to a large spatial extent, graphene’s nonlinear change in material refractive index have little influence on the overall effective waveguide refractive index. This is not the case for the extinction coefficient, as while it is negligible for silicon in the 1.3–1.7 µm spectrum, it is quite substantial for graphene (kgraphene ~3). Hence, any nonlinear change in graphene’s extinction coefficient would show up prominently in the effective waveguide losses. The implication of this result is that the GOS nonlinear waveguide is better suited to be designed as an extinction-based modulator, as we will understand better through further analysis below.Another important point of observation is that the magnitude of the waveguide λ0 is the free-space wavelength. We can also define the nonlinear parameter containing the nonlinear extinction coefficient through modifying the expression toAnother way to quantify the nonlinearity of a waveguide that also takes into account the effective optical mode area is through its nonlinear parameters. The common definition of the nonlinear parameter containing the real nonlinear index is given as−1 m−1, are plotted in Fig. γn is expected to be low since the optical mode interaction with graphene is minute. In Fig. −1 m−1 for the TE mode and an average of 3–10 W−1 m−1 for the TM mode, which is far lower than the typical values for SOI waveguides in the order of 100 W−1m−1. However, an interesting case is observed for γk, which has values of more than two-orders higher than its real counterpart, in the range of 150–400 W−1 m−1 (or 650–1700 dB W−1 m−1) for the TE mode and an average of 300–1000 W−1 m−1 (or 1300–4300 dB W−1 m−1) for the TM mode, as shown in Fig. The nonlinear parameters, both in units WHere we shall study the construct of two types of nonlinear GOS modulator, which are the phase and extinction modulators respectively. For phase modulator, the objective is to perform a π-phase shift for constructive/destructive interference in a Mach-Zehnder interferometer (MZI), so as to achieve maximum contrast between the on/off states. It is also assumed that only one arm of the MZI is covered with graphene to minimize the device’s insertion loss. The maximum phase-shift of such a modulator is given asI implicitly carries the usual saturation terms, while the nonlinear effective length of the waveguide will lengthen according to the optical pump intensity due to the saturable absorption effect. The use of the nonlinear effective waveguide length ensures that the output signal intensity from the GOS waveguide is high enough to combine interferometrically with the signal from the reference arm.Here, On the other hand, for the extinction modulator we can similarly write the maximum extinction change asEF = 0.1 eV and operating wavelength of 1.55 µm. For an MZI phase modulator, the optical signal is split equally to both arms, and only one of the arms is coated with the graphene layer. To determine the minimum optical pump intensity required for the device to perform a π-phase shift, we plot out ∆ϕmax in Fig. I ~ 0.3 GWcm−2, for both the TE and TM modes. The corresponding nonlinear effective waveguide length for these two modes, read from the Leff-nonlinear plot in Fig. To illustrate the design steps of the nonlinear modulators, we first choose an example GOS waveguide, with parameters of graphene ∆αmax in Fig. −2, and the corresponding Leff-nonlinear for the TE and TM modes are 0.22 mm and 0.14 mm respectively, which are at least 70 times shorter than the phase modulator. To accommodate switching of both modes, we pick the shorter waveguide of the two (0.14 mm) to minimize insertion loss for the TM mode. Finally, Fig. −2 pump intensity, the TE mode switches from −8 dB to −3 dB, representing a contrast of 5 dB, while the TM mode switches from −12 dB to −4 dB, a contrast of 8 dB. There is also the possibility of constructing even shorter waveguides by allowing an increase to the pump intensity.On the other hand, the design of the extinction modulator is more straightforward. In a similar fashion, we plot −18 m2 W−1, and Aeff of 2 × 10−13 m2 for the fundamental TE mode, which transcribes to a nonlinear parameter of ~100 W−1 m−1 at the telecommunications wavelength7. Using a waveguide length of 1.5 cm, the required optical intensity to modulate a π-phase shift is 0.86 GW cm−2. The nonlinear GOS phase modulator, in comparison, require a slightly lower optical intensity at 0.3 GW cm−2.A quick performance evaluation could be made for the nonlinear GOS waveguide devices against a typical nonlinear SOI waveguide. The typical 500 nm × 200 nm SOI waveguide have a nonlinear refractive index of 6 × 10−2.In stark contrast to the nonlinear GOS phase modulator, the nonlinear GOS extinction modulator compares very favorably to the typical nonlinear SOI modulator. The nonlinear GOS extinction modulator has a device length 70 times shorter at 0.14 mm and the required optical pump intensity is 80 times lower at 10 MW cm−2), and the saturable absorption phenomenon dominates. However, for higher optical intensities above 10 GW cm−2, it is possible that the two-photon absorption (TPA) process will take over and cause an increase in device optical loss with increasing optical intensity, as evidenced in ref.31. Also, the temporal optical response of graphene is ultrafast, possibly reaching Petahertz (PHz) or sub-femtosecond (sub-fs) timescales from a very recent study32.Throughout the discussion of our simulated results, it is assumed that the optical intensity is low  in direct contact with graphene. Fabrication of such structures may be possible in the near future with advancement of technologies such as wafer transfer and embedding of grapheneWe have studied the use of graphene to enhance the nonlinear properties of an SOI photonic waveguide. Graphene has a giant nonlinear Kerr coefficient which enables all-optical modulation at low optical intensities. Also, its existence as a thin film makes it easily integrated onto current existing SOI waveguide platforms, which is a highly desirable structural property, in contrast to other bulk nonlinear materials where integration requires etching and deposition, or hybrid integration via evanescent coupling to a separate waveguide platform.−2. Direct irradiation of the optical pump on the graphene surface requires very low optical intensities to perform modulation with very high switching contrast of at least 5–8 dB. In addition, GOS waveguide lengths are by far shorter than standard SOI nonlinear waveguides. These performance improvements brought by the integration of graphene on nonlinear silicon photonic waveguides could pave the way for more compact and low-powered all-optical devices for chip-scale integration.The GOS waveguide’s only drawbacks are the high linear absorption and limited access to the photonic waveguide modes. Nonetheless, the high linear absorption of graphene has already been compensated by its high saturable absorption at very low optical intensities in the order of 10 MW cmI = 1 kW cm−2, is separately calculated using data from refs15. The calculated value is added to the linear refractive index for simulation. The difference between the effective indices from the two sets of simulation, neff1 and neff2, would give us the effective index changeTo obtain the effective nonlinear waveguide Kerr index, two sets of effective waveguide indices are obtained using two-dimensional MODE simulations in COMSOL application. In the first set, graphene’s linear refractive index is used in the simulation. In the second set, graphene’s nonlinear change in refractive index for an optical pump intensity, The effective nonlinear waveguide Kerr index is then easily found usingAll data generated or analyzed during this study are included in this published article.


Cancer therapy has been constantly evolving with the hope of finding the most effective agents with the least toxic effects to eradicate tumors. Cancer immunotherapy is currently among the most promising options, fulfilling this hope in a wide range of tumors. Immunotherapy aims to activate immunity to fight cancer in a very specific and targeted manner; however, some abnormal immune reactions known as immune-related adverse events (IRAEs) might occur. Therefore, many researchers are aiming to define the most proper protocols for managing these complications without interfering with the anticancer effect. One of these targeted approaches is the inhibition of the interaction between the checkpoint protein, programmed death-receptor 1 (PD-1), and its ligand, programmed death-ligand 1 (PD-L1), via a class of antibodies known as PD-1/PD-L1 inhibitors. These antibodies achieved prodigious success in a wide range of malignancies, including those where optimal treatment is not yet fully identified. In this review, we have critically explored and discussed the outcome of the latest PD-1 and PD-L1 inhibitor studies in different malignancies compared to standard chemotherapeutic alternatives with a special focus on the clinical efficacy and safety. The approval of the clinical applications of nivolumab, pembrolizumab, atezolizumab, avelumab, and durvalumab in the last few years clearly highlights the hopeful future of PD-1/PD-L1 inhibitors for cancer patients. These promising results of PD-1/PD-L1 inhibitors have encouraged many ongoing preclinical and clinical trials to explore the extent of antitumor activity, clinical efficacy and safety as well as to extend their applications. Cancer therapy has regularly shown glimmers of hope in the search for the most effective measure with the least toxic effects to eradicate tumors. Various approaches have been implemented in cancer therapy, which include surgery, radiation, chemotherapy and targeted therapy. The continuous process of research has shifted the focus in the last century toward immunotherapy as a novel tool for fighting cancer. The concept of utilizing immunity as a therapeutic technique was first introduced in 1957 by Thomas and Burnett, who discussed the ability of tumors to provoke an immune response ,3. Thus,The growing evidence on the role of immunity in treating cancer has given rise to multiple strategies such as the inhibition of cancer checkpoint proteins. Checkpoint proteins are considered a vital part of the immune system expressed on different immune cells with the ability to initiate an immune response either by their activation or inhibition . In 1997The activation of checkpoint proteins expressed on T-lymphocytes such as cytotoxic T-lymphocyte antigen 4 (CTLA-4) and PD-1, usually helps the tumor cells to escape detection by the immune system. Thus, the inhibition of these checkpoint proteins would activate the immune system against tumors . Compare+ cytotoxic T cells from inducing an anti-tumor response. Thus, tumors would acquire an adaptive resistance through PD-L1 upregulation, which is one of the obstacles against the application of PD-1/PD-L1 inhibitors .,25.23,25Other studies were performed to explore the effect of nivolumab in NSCLC treatment. Some of these trials assessed its efficacy as a second-line treatment upon the initiation of other types of therapy. The latest related preformed trials are the CheckMate 017 and CheckMate 57 ,29. BothThese findings were the reasons behind the FDA approval of nivolumab use as a second-line treatment in advanced NSCLC, in 2015 . FurtherPembrolizumab MK-3475) is an IgG-1 mAb that is considered to be a highly potent and selective PD-1 inhibitor ; it was 75 is an The efficacy and safety of pembrolizumab as a first-line agent in NSCLC gave more promising results than nivolumab against chemotherapy. The ORR with pembrolizumab as a first-line therapy was 44.8%. However, the ORR of the docetaxel-treated group was only 27.8% with 2.2 months as the median time of response to both groups . StudiesThe antitumor efficacy of pembrolizumab according to the results of the KEYNOTE-012 study was durable; it revealed a good response rate. About 33 urothelial cancer patients were enrolled in this phase IB study to receive pembrolizumab at a dose of 10 mg/kg every two weeks. The retrieved ORR was 38% among the PD-L1-positive patients and 5% of the pembrolizumab-treated patients displayed grade 3–4 adverse effects .Currently, a phase II study (KEYNOTE-052) is running, in which urothelial cancer patients are enrolled to receive pembrolizumab as a first-line agent . If thisMM is another FDA approved indication of pembrolizumab as an anticancer agent. In KEYNOTE-002, a phase II clinical trial , pembrolFurthermore, the efficacy of pembrolizumab in MM patients was demonstrated in another large phase I clinical trial, which enrolled MM patients to receive pembrolizumab at a dose of 2 mg/kg or 10 mg/kg once every two or three weeks . The higA similar phase IB study (KEYNOTE-028), which was performed in PD-L1-positive ovarian cancer patients, provided promising preliminary results. Among the 26 enrolled patients, one patient achieved a complete response and two patients showed partial response after treatment with 10 mg/kg of pembrolizumab once every two weeks. The best OR was 11.5% and all patients experienced ≥1 adverse events such as fatigue, anemia and decreased appetite . Thus, fPembrolizumab applications suggest certain similarities to nivolumab-reported studies and findings. Both agents share comparable results in terms of their clinical efficacy in certain tumor types such as in melanoma, in addition to the fact that both were the first FDA approved checkpoint inhibitors for the same indications . HoweverPidilizumab (CT-011) is an IgG-1 mAb that targets PD-1 protein . The effBesides pidilizumab activity in hematological malignancies, a phase II clinical trial revealed its powerful activity in refractory cases of melanoma . In thisAMP-224 is a fusion protein composed of the programmed death-ligand 2 (PD-L2) extracellular region and the fragment crystallizable (FC) region of the human IgG-2A  63]. Un. Un63]. Therefore, AMP-224 might exhibit distinct safety and efficacy results as an anticancer agent compared to other PD-1 inhibitors, due to the differences in their biological nature and mechanisms of action. An ongoing study in solid tumors has shown promising tolerance in one patient to a dose of 30 mg/kg. Thus, more crucial outcomes are expected to be revealed by the end of the study . Other rAmong the specific reactions seen with the use of AMP-224 was infusion reactions, which can be explained by the unique nature of this agent . This phAMP-514 is another PD-L2 fusion protein that aims to activate immune defense cells by blocking PD-1 . This agAtezolizumab (MPDL3280A/RG7446) is an IgG-1 humanized antibody that blocks the PD-1/PD-L1 interaction, by targeting the expressed PD-L1 on numerous kinds of malignant cells . The bloIn 2016, atezolizumab became the first agent to gain FDA approval as a second-line treatment of urothelial cancer. This approval was based on the results of a cohort study that enrolled 310 urothelial cancer patients, previously treated with chemotherapy . Atezolip = 0.04) . Am. Am82]. 6 is a huMoreover, durvalumab was extensively studied in urothelial cancer. A phase IB study reported its efficacy in advanced urothelial bladder cancer patients with an ORR of 31%. Furthermore, a good safety profile was attained in this trial as the most reported side effects were fatigue and decreased appetite and only 4% of these patients showed grade 3 treatment-related adverse events . These pThe continued success of this agent encouraged the researchers to explore its efficacy and potential anti-cancer activity in several treatment combinations, aiming to come up with the optimum cure. However, the safety of this agent is still not fully guaranteed as its combination with other agents increased the potential toxicity. For example, an administered combination of durvalumab with a CTLA-4 inhibitor, tremelimumab, resulted in inflammatory myopathy in a 68-year-old NSCLC patient; fortunately, this adverse effect was resolved upon the discontinuation of this regimen .Avelumab (MSB0010718C) is a distinguished IgG-1 antibody that inhibits PD-L1 . It diffThe JAVELIN solid tumor studies include a phase IB trial in metastatic urothelial cancer (MUC), which showed impressive outcomes. Avelumab was administered as a second-line treatment to 44 MUC patients and resulted in an ORR of 40%, in addition to 12 weeks PFS of 70%. Similar to durvalumab, these positive findings in the management of MUC by avelumab pushed the FDA to accelerate its approval as a second-line treatment .The most exciting fact revealed about avelumab is its astonishing efficacy in a very aggressive immunogenic skin cancer type called mMCC. In March 2017, avelumab succeeded in obtaining FDA approval as an anti-cancer agent to cure mMCC . The JAVBeyond any doubt, avelumab is one of the unique PD-L1 inhibitors that tapered difficult malignancies such as mMMC, and it gave hope to mMMC patients after the absence of approved treatments for a long period. Most of the research on avelumab is still in progress, just like other PD-1/PD-Ll agents; the complete picture of this promising agent is yet to be presented as it might be the answer to many more pressing problems in the oncology field.Targeting PD-1/PD-L1 axes in an attempt to eradicate malignancies, via the activation of the immune system, demonstrated great success in numerous types of tumors. To date, the cumulative research efforts lead to the use of PD-1/PD-L1 inhibitors as official FDA approved agents in many tumors such as MUC, NSCLC, MM and MCC. In fact, the clinical field is very active nowadays, running trials to further evaluate the safety and efficacy of these agents . It is nWhen it comes to comparing PD-1/PD-L1 inhibitors to classical chemotherapeutic agents, it is clearly observed that some of them can be considered as equals. This was revealed in multiple reported studies of PD-1/PD-L1 inhibitors such as nivolumab and pembrolizumab, which presented similar, and in some cases even higher, responses regarding the potency in addition to being safer in different malignancies compared to standard chemotherapeutic agents ,53. HoweIn addition, the use of PD-1/PD-L1 agents is not as well established as the detailed defined use of chemotherapy. In fact, many trials are currently running with the aim of identifying the safest dosage regimens and establishing the most potent and proper combination of the PD-1/PD-L1 inhibitors with chemotherapy or any other known treatment for cancer. These combinations could be a therapeutic option with outstanding results, but the low safety might be the limiting factor, which is an obstacle that many trials are trying to solve. Another drawback against the application of these antibodies is the incidence of IRAEs, which can lead to fatal events on rare occasions and so cannot guarantee the safety of the patients.The low expression of PD-L1 in cancer cells is another limitation for the use of PD-1/PD-L1 inhibitors due to the direct correlation between the expression level of PD-L1 and therapeutic response. Therefore, the lower the level of PD-L1, the less the expected therapeutic outcome. Many studies have shown that the patient’s response to these agents depends on the level of the PD-L1 expression. This fact was illustrated by collective reports which showed that out of 1400 essayed patients, response was noted in 45% of the PD-L1-positive patients, while in the PD-L1-negative patients, only 15% showed a similar response. Hence, this offers certain selectivity regarding the responsiveness of patients to the use of PD-1/PD-L1 inhibitors ,90.Since these agents target immunity, they may result in abnormal immune reactions and generate toxicity that affects the skin, gut, lung, liver and other tissues . Among tIn conclusion, based on the reported basic and translational studies, the continuous research and development of PD-1/PD-L1 inhibitors has fostered breakthrough findings in the treatment of challenging tumors. Considering the safety of these agents, PD-1/PD-L1 inhibitors are generally better tolerated than classical chemotherapeutic agents. Nevertheless, more preclinical and clinical investigations are required to elucidate the key mechanisms and predictive biomarkers of the efficacy and safety of these agents and to limit the risk of IRAEs.


The role of hydrochloric acid treatment on the exfoliation result was carefully examined. The exfoliated products were characterized by X-ray diffraction (XRD) patterns, scanning electron microscopy (SEM), atomic force microscopy (AFM), and UV-Vis spectroscopy. The exfoliated g-C3N4 nanosheets exhibited a uniform thickness of about 3–5 nm and a lateral size of about 1–2 µm. A g-C3N4/graphene nanocomposite was prepared via a self-assembly process and was demonstrated to be a promising sensing material for detecting nitrogen dioxide gas at room temperature. The nanocomposite sensor exhibited better recovery as well as two-times the response compared to pure graphene sensor. The detailed sensing mechanism was then proposed.Graphitic carbon nitride (g-C Gas sensors are devices that able to respond to specific gasses and they play an important role in industrial chemical processing, environmental monitoring, agriculture, medicine, public safety, and indoor air quality control . Up to nRecent studies have revealed that two-dimensional (2D) materials, especially graphene, have the potential to detect numerous gases at room temperature owing to their large surface area, high carrier mobility, and low noise. However, many reports have also demonstrated that pristine graphene has a poor gas sensing property owing to the absence of dangling bonds in the structure ,9. In or3N4), as another emerging component with a two-dimensional characteristic structure has attracted considerable attention recently, due to the tri-s-triazine units that are connected by amino groups in each layer and the weak van der Waals forces between layers. The presence of nitrogen atoms in the graphene-like layered g-C3N4 structure gives g-C3N4 its unique properties, such as semiconductor properties, solid alkalinity, and complexing ability, thus endowing it with better performance than graphene in some aspects [3N4 has been extensively used as a polymeric photo-catalyst for solar hydrogen production and environmental purification, as well as oxygen reduction and evolution [3N4 exhibits excellent gas sensing properties owing to its excellent catalytic property [3N4 and graphene, a synergetic effect in sensing performance could be expected if the two components are composited as a gas sensor material.On the other hand, graphitic carbon nitride  or nitric acid (HNO3) was adopted to intercalate the acid ions into the interlayer space of g-C3N4 followed by an ultrasonic treatment, and ultrathin g-C3N4 nanosheets were successfully synthesized [3N4. Moreover, in these previous studies, the controlling factors in the exfoliation process, such as acid treatment time, were rarely considered.Up to now, the lack of a simple approach to producing 2D nanomaterials at a large scale has been the main obstacle to achieving wide application of 2D graphene-like materials. The feasibility of the recently developed ultrasound-assisted liquid-phase exfoliation method has been demonstrated for producing ultrathin nanosheets from bulk 2D material. The cavitation effect induced by the collapse of ultrasonic-produced bubbles generates liquid jets with high temperature, pressure, and speed, which would overcome the interlayer van der Waals force and break up the layered structure to yield individual nanosheets. However, this method is still not robust enough owing to the low yield and re-aggregation tendency after exfoliation. To address these issues, a possible route is the optimization of the solvent. It is reported that the maximization of exfoliation efficiency is related to the surface energy of the solvent. The comparative surface energy between the solvent and the 2D structured solute is favorable for the delamination. Xie and her co-researchers revealed that the surface energy of water matches well with that of g-Cin water . Anotherthesized ,28. Howe3N4 and g-C3N4 products exfoliated with different HCl acid treatment times were examined by X-ray diffraction (XRD) patterns. As shown in 3N4 and the resultant g-C3N4 products remain substantially the same except for some minor changes. No obvious difference was observed between the exfoliated products. All the samples presented a characteristic peak near 27.7°, which can be indexed to the (002) facet caused by the interlayer stacking reflection of conjugated aromatic systems. It was found that the (002) peaks of exfoliated g-C3N4 presented a slight left shift from 27.7° to 27.5°, suggesting loose packing in the exfoliated g-C3N4 product. It is worth noting that the intensity of the (002) peak decreased significantly in the exfoliated sample compared with the bulk sample, demonstrating the successful exfoliation of bulk g-C3N4. It was also observed that the sensitivity of the diffraction peak at 12.74°, which represents the period tri-s-triazine group, was reduced in the exfoliated g-C3N4 compared with the bulk g-C3N4. This could be attributed to the downgrade of the planar size after exfoliation.The crystal structures of bulk g-C3N4 displayed photoabsorption from ultraviolet to visible light. The bulk g-C3N4 has a band edge at approximately 460 nm corresponding to 2.70 eV. For comparison, all the exfoliated g-C3N4 samples have a band edge at approximately 450 nm, corresponding to a bandgap of 2.74 eV, indicating a slight blue shift of 0.04 eV. The increase of bandgap after exfoliation can be attributed to the well-known quantum confinement effect. When the thickness of the g-C3N4 product after exfoliation becomes ultrathin, approaching the dimension of the de Broglie wavelength, the motion of electrons is confined, leading to the splitting of energy levels, and thus the conduction and valence bands shift in opposite directions, resulting in the increase of the bandgap energy.The light absorbance of the samples was studied by UV-Vis spectroscopy. As shown in 3N4 products. According to the Lambert-Beer law of A/l = αC, where α is absorption coefficient, A is the absorbance, l is light path length, and C is the concentration of solute, the absorption of light is directly proportional to both the concentration of the solute and the thickness of the medium in the light path. Given that the light path was fixed throughout the measurement, the concentration of g-C3N4 could be estimated from the intensity of absorption. As observed from 3N4 product with 0.5 h acid treatment exhibited the lowest concentration. The concentration increased considerably as the acid treatment time extended to 1 h, and then slightly increased as the time further increased to 2 h, suggesting the exfoliation approached saturation.The UV-Vis absorption spectra of the samples also provide information of the concentration of the g-C3N4 with 1 h HCl acid treatment was investigated using atomic force microscopy (AFM). As shown in 3N4 nanostructure was observed. The thickness of the g-C3N4 nanosheet was estimated to be about 4 nm . 3N4, respectively. A large number of loosely stacked graphene nanosheets could be observed, suggesting successful exfoliation. On the other hand, the exfoliated g-C3N4 nanosheets exhibited a severe restacking, whereby it is difficult to identify an individual nanosheet. In the case of the composite, as shown in 3N4/graphene film was observed. Remarkably, the restacking phenomenon of g-C3N4 was greatly alleviated, which could be attributed to the self-assembly process between g-C3N4 and graphene [3N4/graphene composite.The microstructures of the graphene and g-Cgraphene . This fi3N4/graphene composite, respectively. The elemental mapping analysis, as shown in 3N4 [Energy-dispersive X-ray spectroscopy (EDS) analysis and elemental mapping were also utilized to investigate the elemental composition and distribution of the g-Cn in 3N4 .3N4/graphene nanocomposite, as displayed in 2O [2 C=C, respectively [2 hybridized aromatic N bonded to carbon atoms (C=N–C) existed in g-C3N4, which was known as the reactive pyridine N. Besides, the surface N/C ratio in nanocomposite was determined to be 0.27, which is closed to that in EDS analysis. The above XPS results further demonstrated the formation of g-C3N4/graphene nanocomposite.X-ray photoelectron spectroscopy (XPS) measurement was carried out to further study the chemical composition and element binding energies of g-Ced in 2O ,31,32. Tectively ,29. No C3N4/graphene composite gas sensor was examined with NO2 gas. The pure graphene sensor as a control sample was also tested simultaneously. 2 at room temperature. As observed, upon exposure to NO2 gas, the resistance of both sensors decreased, suggesting a p-type behavior. It is known that NO2 as a typical electron withdrawer would increase the hole concentration of the sensor materials, and thus decrease (or increase) the resistance of p-type (or n-type) semiconductors. Remarkably, the composite sensor exhibited two-times the response of pure graphene, indicating that the incorporation of g-C3N4 would benefit the sensing performance of the graphene sensor.The performance of the g-C2 gas was removed, while about 20% recovery was observed in the composite sensor within 200 s. This is possibly attributed to the thermal excitation of g-C3N4 that introduced active carriers and facilitated the desorption process of NO2 gas molecules. Our results indicate that the incorporation of specific semiconductors can achieve full recovery of the graphene sensor without the need for a complicated heating or vacuum process.It is well-known that intrinsic graphene shows poor recovery, partially due to the strong adsorption energy of the gas molecule. Thus, heating at an elevated temperature or vacuum treatments are required to clean the graphene sensor ,34,35. A3N4/graphene composite sensors toward NO2 ranging from 5 to 200 ppm. The sensors responded well with the target gas. The responses increased monodirectionally as the concentration of NO2 increased. No obvious saturation state was observed in the composite sensor, suggesting a broad detection range. Remarkably, the composite sensor showed two-times more response than the other sensors to pure graphene in all the tests. The stability property of our nanocomposite sensor was also examined as shown in 2, suggesting an excellent repeatability.3N4/graphene composite sensor is proposed, as schematically shown 3N4 nanosheet behaves similarly to a base that is ready to interact with the oxidized NO2 gas molecules. This characteristic of g-C3N4 nanosheet as well as its excellent catalytic property endows it with a promising capacity for the adsorption of NO2 molecules. On the other hand, graphene with superior carrier mobility would act similarly to a signal highway in the sensing process. Upon adsorption, the oxidized NO2 gas molecule with strong electron affinity deposits a hole in the g-C3N4 nanosheet. These hole carriers are then rapidly conducted by the graphene. In short, the complementary natures of g-C3N4 and graphene in the sensing process introduce a synergetic effect that contributes to the excellent sensing property of the nanocomposite sensor. In addition, considering the different roles of both materials in the sensing process, a tradeoff on the sensing performance would be expected if the composition of the composite is changed. Through systematic investigation, an optimized ratio of g-C3N4 and graphene could be achieved to obtain a high-performance sensor with excellent sensitivity and promising recovery property. This is the expected direction in the future research.The sensing mechanism of the g-CRaw melamine purchased from Sigma-Aldrich Korea Ltd.  was used as received. The fabrication process was modified from the reported methods ,37,38. T3N4 powder was added to 25 mL hydrochloric acid  and stirred for 1 h. The obtained transparent yellow dispersion was then filtrated and washed repeatedly with water until the pH value became neutral, followed by a drying process at 100 °C for 6 h. This acid-treated powder was re-dispersed in 200 mL deionized (DI) water, followed by sonication treatment for 2 h in an ultrasonic bath . Subsequently, the mixture was centrifuged at 8000 rpm for 10 min to remove the residual un-exfoliated g-C3N4 particles. Finally, a light white suspension was obtained. In order to determine the concentration of the product, 100 mL of g-C3N4 dispersion was transferred to a pre-weighted vial and dried in an oven at 100 °C for 24 h. The concentration of g-C3N4 in dispersion after 1 h acid treatment was determined to be about 50 μg/mL.In a typical synthesis, 0.5 g of yellow bulk g-CGraphene was prepared following the process developed in our previous work . Briefly3N4 and graphene were mixed with ultrasonic treatment for 1 h to achieve complete mixing. After mixing, the mixture was evaporated in an oven for 24 h at a moderate temperature (~60 °C) to improve the concentration of solute without introducing severe aggregation. Alumina substrates (4 × 4 mm) with interdigital Pt electrodes were carefully cleaned and placed on a hot-plate with a temperature of about 100 °C. Concentrated solution was then drop-casted onto the sensor substrates using micro-pipettes. The thickness of the thin films was about 1 µm and was controlled by the volume of the solution in the micro-pipettes. After coating, the alumina substrates were heated at 100 °C in an oven for 1 h to eliminate the remaining solvent and then sintered at 200 °C in Ar gas for 1 h to improve the adhesion and contact. Pure graphene-based sensor as the control sample was also prepared using the same method.Two as-prepared dispersions containing equivalent weights of g-C3. Nitrogen gas was used as the carrier gas. NO2 gas with a starting concentration of 500 ± 1 ppm in nitrogen was used as the target gas. The accurate concentration control of the target gas was achieved by using a mixing system equipped with mass flow controllers  and mass flow meters. All the measurements were conducted under ambient condition. The total gas flow of the carrier and target gases was kept at 250 sccm throughout the measurement process. The electrical conductance signal of the sensors was collected and recorded by data acquisition  through a customized clamp and wire connector. The sensing response was defined as:NR and GR represented the resistance of the sensors upon exposure to nitrogen and target gas, respectively.The sensors were placed in a stainless chamber having a total volume of 10 cm3N4 or g-C3N4/graphene nanocomposite onto an oxidized silicon wafer, followed by a drying process at 80 °C for 12 h. X-ray diffraction (XRD) was performed using a Rigaku RINT2200 X-ray diffractometer  with monochromatized Cu-Kα radiation. Atomic force microscopy (AFM) measurements were carried out on a Bruker MutiMode-8 system . The microstructure, morphology, and elemental distribution of the samples were systematically investigated by Raman spectroscopy , Scanning Electron Microscopy , and Energy-dispersive X-ray spectroscopy (EDS) mapping (co-equipped with SEM) , respectively. Chemical compositions and element binding energies were analyzed using X-ray photoelectron spectroscopy (XPS) on an Ulvac-phi Veresprobe II system  with monochromatic Al Kα as an excitation source. The absorption spectroscopy measurements were performed using a Varian Cary 6000i and a 1 cm cuvette.For material characterization, samples were prepared by drop-casting the solution containing g-C3N4 nanosheets from bulk g-C3N4 using a facile HCl acid treatment followed by an ultrasonic process. The effect of acid treatment on the exfoliation result was carefully examined. The exfoliated g-C3N4 nanosheets exhibited a uniform thickness of about 3–5 nm and a lateral size of about 1–2 µm. g-C3N4/graphene nanocomposite was prepared via a self-assembly process. Remarkably, the restacking phenomenon of g-C3N4 was greatly alleviated after compositing with graphene. A promising sensing performance of g-C3N4/graphene nanocomposite toward NO2 gas at room temperature was demonstrated. The nanocomposite sensor exhibited better recovery as well as two-times the response compared to the pure graphene sensor. The promising performance of the nanocomposite sensor was attributed to a synergetic effect in which the graphene with superior carrier mobility acts as the signal pathway, while the g-C3N4 nanosheet, with an active surface, plays the role of analyte acceptor.In summary, we successfully prepared g-C


The use of antibodies to target immune checkpoints, particularly PD-1/PD-L1, has made a profound impact in the field of cancer immunotherapy. Here, we identified KN035, an anti-PD-L1 nanobody that can strongly induce T-cell responses and inhibit tumor growth. The crystal structures of KN035 complexed with PD-L1 and free PD-L1, solved here at 1.7 and 2.7 Å resolution, respectively, show that KN035 competes with PD-1 (programmed death protein 1) for the same flat surface on PD-L1, mainly through a single surface loop of 21 amino acids. This loop forms two short helices and develops key hydrophobic and ionic interactions with PD-L1 residues, such as Ile54, Tyr56 and Arg113, which are also involved in PD-1 binding. The detailed mutagenesis study identified the hotspot residues of the PD-L1 surface and provides an explanation for the stronger (~1 000-fold) binding of KN035 to PD-L1 than PD-1 and its lack of binding to PD-L2. Overall, this study reveals how a single immunoglobulin-variable scaffold of KN035 or PD-1 can bind to a flat protein surface through either a single surface loop or beta-sheet strands; and provides a basis for designing new immune checkpoint blockers and generating bi-specific antibodies for combination therapy. Immune checkpoints are inhibitory pathways of the immune system that maintain self-tolerance and prevent autoimmunity . The PD-−/− mice do not express PD-L2, leading to increased airway hyperactivity and lung inflammation [de novo design of PD-1/PD-L1 inhibitors.However, these immune checkpoints are often upregulated by tumor cells to induce local immune suppression and attenuate the endogenous antitumor immune response , 17. Forammation . Therefoammation ,  21, leammation . Here, wammation , designaammation , 26. NotKd value of 3.0 nM  from pre-formed PD-1/PD-L1 complexes slightly more effectively than durvalumab   and screened the heavy-chain-only nanobody phage library derived from a PBMC  with conventional panning technology . One of f 3.0 nM . KN035-Ff 3.0 nM . KN035-Frvalumab , which iin vitro . As KN03rization  was chos dosages , which ivalumab) . These rN-terminal immunoglobulin-variable domain of PD-L1 at 1.7 Å resolution and with free PD-L1 at 2.7 Å resolution. The models were built and refined to obtain good geometry   geometry . The crygeometry . The oveys111.3) , and the2  were isolated 1 week after the last immunization. The sequence corresponding to the variable domains of the heavy-chain antibodies was amplified with specific primers and used to create a nanobody phage display library. Enrichment screening against PD-L1-Fc was performed in 96-well plates coated with 10 μg of protein per well. High-affinity bacteriophages were obtained after 4 rounds of screening. Ninety-six individual colonies were randomly selected and amplified in culture. Positive colonies verified by ELISA (enzyme-linked immunosorbent assay) were sequenced and defined. The nanobody coding genes were cloned into pET-32b  and expressed in Escherichia coli. The nanobodies were purified and screened for their ability to block the interaction between PD-L1 and PD-1 by performing a competitive ELISA. One of the nanobodies showing strong activity in blocking the PD-L1/PD-1 interaction was termed KN035. The coding DNA sequence for KN035 was fused with that of the coding fragment for human IgG1 Fc (KN035-Fc) and cloned into vector pcDNA3.1. KN035-Fc was expressed in HEK293 cells and secreted in culture medium. It was purified to homogeneity (>95%) by performing Protein A affinity chromatography .An anti-PD-L1 nanobody was produced and purified as previously described . In brie2 atmosphere for 2–3 h. After incubation, all the suspension cells were carefully removed, and the medium was changed to complete Roswell Park Memorial Institute-1640 medium with 5 ng ml−1 granulocyte-macrophage colony-stimulating factor  and 20 ng ml−1 interleukin-4. The medium was refreshed every 2 days, and 10 ng ml−1 tumor necrosis factor-α was added on the 4th day. Finally, the mature dendritic cells were harvested for mixed lymphocyte culture reaction experiments on the 5th day. CD4+ T cells (1×105) and allogeneic dendritic cells (1×104) were co-cultured with or without dose titrations of KN035-Fc or the control antibody or durvalumab [t-tests.PBMCs were obtained from heparinized peripheral blood samples of healthy donors using Ficoll–Hypaque density gradient centrifugation . Freshlyrvalumab , 48. Thein vivo, a xenograft mouse model [6 A375-PD-L1 cells (50 μl) and 1×106 human PBMCs (50 μl) [−1 and 0.037, 0.18 or 0.92 mg kg−1, respectively (same molar amount for both). Tumor volumes were measured along three orthogonal axes  and calculated as tumor volume=(abc)/2. Mice with tumor volumes larger than 2 000 mm3 were killed by CO2 administration. Statistical analyses were performed using GraphPad Prism software . The in vivo activity of KN035-Fc and durvalumab were also tested on a B16-PD-L1/C57 mouse model; however, both antibodies showed limited tumor-suppressing effect at the same dosages.To evaluate the antitumor effect of KN035-Fc se model , 47 was E. coli BL21 (DE3) as inclusion bodies. Cells were cultured at 37 °C in Lysogeny broth and induced with 0.5 mM IPTG  until the optical density at 600 nm reached 1.0. After a further 16-h incubation at 37 °C, the cells were collected by centrifugation, resuspended in lysis buffer  and lyzed by sonication. Inclusion bodies were recovered by centrifugation at 15 000 g for 10 min and were then washed three times with lysis buffer, followed by washing without Triton X-100. The inclusion bodies were dissolved in 20 mM Tris, pH 7.4, containing 6 m GuHCl, 0.5 mM ethylenediaminetetraacetic acid and 10 mM dithiothreitol. The solubilized fraction was clarified by centrifugation and dialyzed against 10 mM HCl to remove dithiothreitol. After dialysis, the sample was redissolved in 6 M GuHCl and added drop-wise into a refolding buffer consisting of 1 m Arg hydrochloride, 0.1 m Tris, pH 8.0, 2 mM ethylenediaminetetraacetic acid, 0.25 mM oxidized glutathione and 0.25 mM reduced glutathione. After incubation at 4 °C overnight, the complex was dialyzed against 10 mM Tris, pH 8.0 and purified to homogeneity using a HisTrap Ni-Sepharose column, HiTrap SP ion-exchange column and Superdex 75 . Other PD-L1 variants, such as I54A, Y56A, E58A, D61A, N63A, Q66A, V68A, R113A, M115A, S117A, Y123A and R125A, were prepared using the same procedure. For the preparation of the PD-L1/KN035 complex, the N-terminal IgV domain of PD-L1 (amino acids 19–132) was similarly cloned into pET-28a and expressed in E. coli as PD-L1. Refolding was performed in refolding buffer containing 0.1 mg ml−1 of KN035. The PD-L1 IgV domain/KN035 complexes were subsequently purified using ion-exchange and gel filtration columns .Genes encoding human PD-L1 (amino acids 19–239) were cloned into pET-28a. Proteins were expressed with a C-terminal His-tag in −1 and screened for crystallization conditions using commercially available buffer with sitting-drop vapor diffusion; 0.2 μl of the protein complex solution was mixed with 0.2 μl of reservoir solution. Diffraction-quality crystals of PD-L1-IgV/KN035 were obtained at room temperature from 1.4 m ammonium sulfate and 2 m sodium chloride after optimization. The crystals of PD-L1 were grown with a precipitation solution of 0.2 mM ammonium acetate and 20% PEG 3350.Both purified PD-L1 and PD-L1/KN035 complexes were concentrated to ~15 mg mlCrystals were cryoprotected in 20% glycerol in the mother liquor and flash-cooled in liquid nitrogen. Diffraction data were collected on beamlines BL17U1 (SSRF) and BL19U1 (NCPSS), Shanghai, China . The dat–1 KN035 for 40 s before equilibration for 60 s in phosphate-buffered saline with 1% bovine serum albumin. Variants of PD-L1 were prepared as a twofold serial dilution in 0.1% bovine serum albumin and separately incubated with the KN035 bound on the tips for 120 s. Then, the PD-L1 variants were allowed to dissociate for up to 320 seconds depending on the observed dissociation rate. All measurements were corrected for baseline drift by subtracting a control sensor exposed to running buffer only. Data analysis and curve fitting were carried out using Octet software. The affinity of these PD-L1 variants toward PD-1 could not be accurately measured because the affinity between PD-1 and PD-L1 is very low (~6–8 μM) [Kd values of 2.1 nM and 0.84 nM, respectively (data not shown). These Kd values are largely consistent with the Kd (3.0 nM) derived from KN035-Fc fixed on protein A chip, with differences likely arising from avidity and protein-immobilizing methods.A fortéBio Octet K2 instrument was used to measure the binding kinetics of PD-L1 variants to KN035-Fc with protein A sensor . All sen~6–8 μM) , 40, and