dataesr/scientific-paragraphs-categorization huggingface dataset:
Background: Retroviral integration favors weakly conserved palindrome sequences at the sites of viral DNA joining and generates a short (4-6 bp) duplication of host DNA flanking the provirus. We previously determined two key parameters that underlie the target DNA preference for prototype foamy virus (PFV) and human immunodeficiency virus type 1 (HIV-1) integration: flexible pyrimidine (Y)/purine (R) dinucleotide steps at the centers of the integration sites, and base contacts with specific integrase residues, such as Ala188 in PFV integrase and Ser119 in HIV-1 integrase. Here we examined the dinucleotide preference profiles of a range of retroviruses and correlated these findings with respect to length of target site duplication (TSD). Results: Integration datasets covering six viral genera and the three lengths of TSD were accessed from the literature or generated in this work.
In addition to HIV-1  [61, 62] , the lentiviruses simian immunodeficiency virus (SIV)  [63]  and equine infectious anemia virus (EIAV)  [64] , as well as the gammaretrovirus Rev-A  [65, 66] , yield 5 bp TSDs. Perusal of the literature revealed that the number of reported integration site datasets from virus-infected cells ranged from a small handful for Rev-A  [65]  to several million for MoMLV  [21, 22]. Rev-A is of particular interest, as it is a gammaretrovirus with a 5 bp TSD; all other gammaretroviruses yield 4 bp TSDs  [14, 15, 17]. We accordingly initiated this study by determining the sequences of 834 unique integration sites from HEK293T cells infected with a Rev-A viral vector by ligationmediated PCR. The targeting preferences of Rev-A for genomic annotations such as genes, TSSs, CpG islands, and gene density are described toward the end of the Results section.
As the HEK293T DNA was fragmented by digestion with restriction endonucleases AvrII, NheI, and SpeI, a matched random control (MRC) of 282,824 unique sites was produced by selecting random positions in proximity of these restriction sites in human genome build  19 (hg19). Sequences extracted from GenBank (http://www. ncbi. nlm. nih. gov/genbank/) or obtained from the authors of prior studies yielded datasets for the remaining 11 viruses that encompassed from ~170 to 336,000 unique integration sites (Table  1 ). Sequence logos  [67]  were compiled to provide a visualization of base preferences at each nucleotide position at and surrounding the points of vDNA joining for the 12 different viruses (see Figures  1, 2  and 3, A-D ). The position of vDNA insertion on the tDNA plus strand by convention was designated as 0, with upstream and downstream nucleotide positions extending in the negative and positive directions, respectively.
Both PFV and HIV-1 cell-based datasets exhibited cyclical A/T-rich sequences that extended symmetrically outward from the TSD with approximate 10 bp periodicity (Figure  4B , D), as described previously for HIV-1  [42]. These cyclical base preferences, which were absent from in vitro datasets (Figure  4C, E ), and reminiscent of the A/ T-rich periodicity exhibited by nucleosome-bound DNA (Figure  4A ), indicated that PFV and HIV-1 IN select for their preferred local tDNA sequences in the context of nucleosomal DNA during virus infection  [41, 42]  (Figure  4 ). PFV and HIV-1 selected for marginally distinguishable flexibility profiles at integration sites in naked tDNA in vitro versus cellular DNA (Figure  5 ). As discussed above, raw frequencies of YR enrichment and RY avoidance for PFV at dinucleotide +1 equated to 39% and 13%, respectively (Figure  5A, B , blue curves).
The statistical relevance of observed frequencies versus the MRC were determined by Fisher's exact test for RefSeq genes, CpG islands, and TSSs and by Wilcoxon rank-sum test for gene density (P values listed in Additional file 3: Table  S1 ). The results of our analyses of 11 previously profiled retroviruses are in line with those of the prior reports (see Table  1  for the list of references). Distributions relative to CpG islands and TSSs were calculated by counting sites that fell within a 5 kb window (+/-2. 5 kb) of these features, while average gene density was calculated by counting the number of RefSeq genes falling within a 1 Mb window (+/-500 kb) of each integration site, and then averaging this value for the entire dataset. Our MRC dataset revealed that 45. 7% of human DNA comprised RefSeq genes (Table  2 ).
DNA strand transfer activity assay The in vitro concerted integration assays were carried out as previously for described Rev-A IN following removal of the His 6 -tag by site-specific proteolysis  [66]. Briefly, 1 μM Rev-A IN mixed with 0. 5 μM vDNA and 4 nM pGEM-3 tDNA, in 40 μL of 20 mM HEPES pH 7. 4, 50 mM NaCl, 5 mM MgCl 2 , 4 μM ZnCl 2 , and 10 mM DTT, was incubated for 1 h at 37°C with varying concentrations of BRD4 462-720 or BRD4 462-720/L630E (0. 05/0. 15/0. 35/0. 5 μM). Reactions were stopped by adding 25 mM EDTA and 0. 5% SDS, and deproteinized by digestion with proteinase K. Products were precipitated with ethanol and analyzed by electrophoresis through 1. 5% agarose gels. DNA was detected by staining with ethidium bromide. Concerted integration products were measured by band intensity quantification using the Molecular Imager® Gel Doc TM XR+ System with Image Lab software (Bio-Rad).
Statistical analysis An MRC dataset of 282,824 sites was created by selecting random genomic positions in proximity (<500 bp) of a AvrII, NheI or SpeI recognition site. The sequence immediately abutting each random site, truncated to 97 bp or less (to simulate Illumina read length), was subjected to the genomic alignment procedure described above. Differences in nucleotide sequence from random among retroviral integration sites were determined by chisquare analysis relative to the above random control. Statistical differences with respect to YR/RY frequency plots and genomic distribution of integration sites was calculated by Fisher's Exact Test using R  [88].
Acknowledgements We thank  Joseph Dougherty  for the generous gift of pJD215 plasmid DNA. We additionally thank the following individuals for graciously sharing with us the coordinates of the following retroviral integration site datasets:  Frederic Bushman ,  MoMLV  and EIAV;  Charles Bangham , HTLV-1,  Jeroen de Ridder , MMTV. This work was supported by  US National Institutes of Health  grants  AI070042  (to A. E. and P. C. ) and  AI060354  ( Harvard University Center for AIDS Research).
75 The accuracy of any one result can therefore be increased, as shown by Rodríguez-Guzmán et al. 76  or by  Mizusaki and Imada 77  in the closely related path integral renormalization group (PIRG) approach. Recently, Tahara and Imada 78 have combined the symmetry-projected determinant expansion with short-and long-range Jastrow factors within a variational Monte Carlo framework, which may be used to further increase the accuracy. [81]  E. Unrestricted Coupled Cluster -Singles and Doubles (UCCSD) Coupled cluster (CC) theory  [40] [41] [42]  is a ground-state wave function technique. It is widely used in quantum chemistry and often considered the best source of precise data for molecules that are neither too large nor too strongly correlated. Its application to the Hubbard model has been more limited, where it has been used in two different formulations.
7122 for UCCSD, barely visible on the main panel), an indication that correlated metallic states are difficult to capture with these methods. Although not shown, data is available for UCCSD(T) (perturbative inclusion of triples) in the supplemental material,  46  which improves upon the value from UCCSD, and gives E/t = -0. 7272 (-0. 7281) for a 16 × 4 (16 × 8) cluster. Full inclusion of triples (UCCSDT) lowers the 16 × 4 estimate to E/t = -0. 7427. The MRPHF results indicate the need for a much larger MR expansion than that afforded in this work. In this parameter regime, ordered 'stripe' phases might exist. However, the precise form of these stripes is strongly influenced by choice of finite size systems (e. g. width and orientation of the cylinder in DMRG and shape of the cluster in DMET) that are used for the thermodynamic extrapolation and the approximations used to solve that finite system.
We see that as system size is increased, the energy increases rapidly. In Fig. 10  we report the double occupancy vs T. At finite T , the DCA results show a clear rise in D as T decreases from 0. 5t → 0. 25t. However, this trend reverses as T decreases further. A similar behavior is obtained also by using DiagMC, demonstrating that this is a genuine effect present in the Hubbard model. These trends are consistent with the T = 0 data, which lie below all of the DCA data points at finite T. For clarity of presentation we again display this data in the inset and add an arbitrary x-axis offset. We see that finite size effects in DMET are very small, and that the extrapolation of DMET agrees perfectly with AFQMC. Finite sized FN results produce values comparable to to DMRG, DMET and AFQMC. However, extrapolation in FN results in an underestimate of the double occupancy, although within uncertainty.
e. the real part of the self-energy. The top left inset of Fig. 11  shows the convergence of the energy in DCA and two different series of DiagMC, [G (0) ] 2 U and G 2 Γ, for increasing order of the diagrammatic resummations, α. The values obtained from the three techniques are within error bars. The T > 0 values smoothly connect to T = 0 (although a precise comparison is not possible because we lack a quantitative functional form to extrapolate the T > 0 values to T = 0) which we display separately in Fig. 12  where data from DMET, AFQMC (constrained path), UCCSD, MRPHF, FN, and DMRG are shown. In this case, MRPHF and UCCSD are systematically higher in energy from the other techniques. In the case of UCCSD we see larger finite size effects than at U/t = 8. Inclusion of higher orders of excitation (perturbative triples (T), triples T and perturbative quadruples (Q)) suggests that the dominant error is associated with the truncation of the excitation order and not finite size effects.
The deviation of the thermodynamic limit value from AFQMC and DMET is on the order of 2 × 10 -3 t, suggesting that excitations beyond the singles and doubles level are important even in this relatively weak coupling regime. Finally, Fig. 14  shows the double occupancy for these parameters. We see an increase in finite size effects in DCA as we progress to lower temperature. Reasonable agreement with DiagMC is achieved in the double occupancy. At temperatures lower than our lowest temperature, the double occupancy will need to dip, as was the case at U/t = 4, in order for the finite T data to be consistent with T = 0. Similar to the strong coupling case, DF provides only a slight shift to the double occupancy, a minimal improvement over DMFT alone. The ground-state double occupancies are very precisely determined by AFQMC and DMET which are in agreement.
ACKNOWLEDGMENTS We acknowledge the  Simons Foundation  for funding. The work at  Rice University  was supported by  NSF -CHE-1462434. GKC acknowledges funding from the  US Department of Energy  for the development of the DMET method through  DE-SC0010530 , and for its application to the Hubbard model and superconductivity through DE-SC0008624. F. B. and L. F. T. acknowledge support from PRIN 2010 2010LLKJBX. SZ and HS acknowledge support from  NSF  ( DMR-1409510 ) for AFQMC method development. MQ was also supported by  DOE  ( DE-SC0008627 ), AEA by  DOE ER 46932. YD and XWL acknowledge support from  NSFC  ( 11275185 ). The AFQMC calculations were carried out at the  Oak Ridge Leadership Computing Facility  at the  Oak Ridge National Laboratory , and at the computational facilities at the  College of William and Mary.
What could be the factors involved in recruiting Cac1 to DSBs? In the fungus Coprinus, CAF-1 was found to interact with Dmc1, and it was proposed that CAF-1 might be recruited to meiotic recombination intermediates through this interaction, to promote nucleosome assembly  [43]. However, our data do not fit with this model, since we observe CAF-1 recruitment in the absence of Dmc1. An alternative possibility is that it may be recruited through interaction with the related Rad51, but we have found that Cac1 is still recruited in the dmc1Δ rad51Δ double mutant (data not shown). Could CAF-1 be recruited early because meiotic DSBs are programmed DSBs? In this case, Cac1 might be recruited via a recombination protein to ensure it is present at a later step when it is needed. A similar situation is seen for the Mre11 complex that is recruited to hotspots prior to meiotic DSB formation by interacting with some of the DSB proteins  [44, 45].
This work was funded by the  Association pour la Recherche sur le Cancer, la Ligue contre le Cancer, la Fondation pour la Recherche Médicale ,  Electricité de France and Agence Nationale pour la Recherche  ( ANR-11-LABX-0044_DEEP ). E. B. was a recipient of a predoctoral fellowship from  University Pierre & Marie Curie  and from  Association pour la Recherche sur le Cancer. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Afatinib plus SRC kinase inhibitors Preclinical experiments in PC9GR cells, an EGFR mutation-positive NSCLC cell line harboring T790M, have implicated SRC kinase in the resistance to afatinib. In proliferation and apoptosis assays, the SRC kinase inhibitor, dasatinib, sensitized cells to afatinib  [57]. This translated into tumor regression in a PC9GR xenograft mouse model  [57]. The combination of dasatinib and afatinib has also shown synergistic activity against triple-negative breast cancer cell lines  [58]. The combination is currently being assessed in a Phase I trial in patients with NSCLC (NCT01999985, Table  1 ).
Afatinib plus JAK/STAT inhibitors STAT proteins are a family of transcription factors that play a key role in multiple cellular functions and are often constitutively activated in human cancers  [62]. Interestingly, in recent preclinical studies, afatinib has been shown to activate the JAK/STAT pathway in NSCLC cell lines by upregulating the interleukin-6 receptor  [62]. It is thought that this pathway may mediate de novo resistance to afatinib in NSCLC cells harboring T790M. This hypothesis is supported by experiments in a mouse xenograft model of H1975, a human EGFR mutationpositive NSCLC cell line harboring T790M. In these experiments, it was found that afatinib and pyridine-6, a pan-JAK inhibitor, had synergistic antitumor activity  [62]. These findings provided rationale for a planned Phase I clinical study that will assess afatinib plus ruxolitinib, a pan-JAK inhibitor, in patients with pretreated advanced NSCLC (NCT02145637; Table  1 ).
An ongoing Phase Ib trial is assessing the combination of afatinib and BI836845, an IGF-1 neutralizing antibody, in patients with EGFR mutation-positive NSCLC with progression following a prior EGFR-TKI (NCT02191891;  Such combinations have shown preclinical activity in other tumor types. For example, the combination of afatinib plus ICR62, an EGFR antibody, potently inhibited proliferation of CRC cells  [72]. Although the mechanism by which the combination of afatinib and EGFR antibodies confers potent antitumor activity in vivo has not been fully elucidated, the combination appears to have synergistic effects on the inhibition of EGFR, HER2, ErbB3 and Erk and Akt phosphorylation  [71]. The broad inhibitory profile offered with afatinib appears to cooperate with anti-EGFR antibodies to overcome recognized mechanisms of resistance to single-agent EGFR inhibitors, including the accrual of T790M and HER2 amplification  [70, 71].
As well as studies in patients with acquired resistance to erlotinib/ gefitinib, an ongoing Phase II/III study is assessing the combination of afatinib and cetuximab, versus afatinib alone, in a frontline setting in patients with EGFR mutation-positive NSCLC (NCT02438722; Table  1 ). The combination is also being assessed in other tumor types. A Phase II trial is assessing afatinib plus cetuximab versus cetuximab alone in patients with chemotherapy-refractory wild-type KR AS metastatic CRC (NCT01919879).
As well as in breast cancer, the combination of afatinib and trastuzumab is currently being assessed in other tumor types. For example, an ongoing Phase II trial is assessing the combination in patients with advanced HER2-positive trastuzumab-refractory esophagogastric cancer (NCT01522768; Table  1 ); preliminary data from this trial indicated that afatinib monotherapy was well tolerated and showed clinical activity in this setting  [89] ; the addition of trastuzumab to afatinib was mandated in a protocol amendment.
Ongoing or planned clinical trials are assessing the combination of afatinib with immunotherapies. Afatinib plus pembrolizumab, a PD-1 inhibitor, is being assessed in an ongoing Phase I study in patients with NSCLC (NCT02364609; Table  1 ). Indeed, combination of immune therapy and afatinib in SCC could be interesting given the recently observed efficacy of the two treatment modalities in this indication  [20, 93]. As another approach, a clinical development program is planned that will assess the combination of afatinib with a self-adjuvanted mRNA vaccine (CV9202) in patients with NSCLC. CV9202 targets six antigens commonly expressed in NSCLC  [101].
Addition of afatinib to paclitaxel-based induction regimens has also been assessed in other clinical trials. A Phase I study assessed the combination of afatinib plus paclitaxel and cisplatin in patients with advanced solid tumors (Table  1 )  [50]. The MTD was determined as continuous afatinib 20 mg/day, paclitaxel 175 mg/m 2 on day 1 and 75 mg/m 2 cisplatin on day 1 of 21-day cycles. Antitumor activity with this combination was promising. Of 26 treated patients, five (19%) responded, including two CRs (both with HNSCC) and disease control was observed in 54% of patients. The most common AEs were diarrhea (89%), nausea (85%), anemia (62%) and fatigue (62%). Other, ongoing, early-phase studies are assessing afatinib/paclitaxel/carboplatin-based regimens as induction therapy in patients with HNSCC (NCT01732640) and oropharyngeal SCC (NCT01721525).
In 21 patients treated, the DCR was 29% of patients, including one CR and four unconfirmed PRs. The most common grade ≥3 AEs were decreased appetite (43%), vomiting (33%) and fatigue (29%). This combination regimen is currently being assessed in an ongoing Phase II trial in patients with inoperable gastric cancer (NCT01743365; Table  1 ). A Phase I dose escalation trial has assessed the combination of afatinib (both pulsed-dose and continuous) in combination with pemetrexed in patients with advanced solid tumors  [55]. The MTD was identified as continuous afatinib 30 mg/day and pemetrexed 500 mg/m 2 on day 1 of a 21-day cycle. Of 23 patients treated, seven (30%) had disease control, including one confirmed PR. The most frequent drug-related AEs were diarrhea (91%), stomatitis (60%), rash (55%) and fatigue (55%).
grade ≥3 (%) Ref. Inhibitors of other growth factor receptors (cont. ) [45] [46] [47] [48] PR: 11 Diarrhea: 94/50 SD: 28 Rash: 56/0 Fatigue: 56/0 Nausea: 50/0 Ongoing Ongoing pCR: 70 Diarrhea: 71/5 Rash: 52/0 Mucositis: 31/0 Fatigue: 26/0 Ongoing Ongoing Planned Planned OR: 0 Diarrhea: 74/NR SD: 45 Neutropenia: 65/NR Rash: 39/NR OR: 13 Alopecia: 50/0 SD: 23 Diarrhea: 50/5 Stomatitis: 50/0 Rash: 40/0 PR: 31 Diarrhea: 94/0 SD: 13 Fatigue: 81/13 Rash/acne: 81/6 Mucosal inflammation:69/6 Decreased appetite: 69/0 Afatinib: 20 mg/day Trastuzumab: 4 mg/kg week 1; 2 mg/kg week thereafter Ongoing Afatinib: 20 mg/day Trastuzumab: 6 mg/kg/3 weeks for 6 weeks, followed by afatinib, trastuzumab and paclitaxel (80 mg/m 2 /week) for 12 weeks followed by epirubicin, cyclophosphamide and trastuzumab Ongoing Planned Afatinib: 20 mg/day (days 2-21) Docetaxel: 75 mg/m 2 (day 1) 21-day cycle Afatinib: 90 mg/day (days 2-4) (day 1) Docetaxel: 75 mg/m 2 21-day cycle Afatinib: 40 mg/day (days 1, 8, 15) Paclitaxel: 80 mg/m 2 28-day cycle 18 65 31 40 16 HER2-positive advanced breast cancer HER2-positive metastatic breast cancer Untreated HER2-positive breast cancer Advanced HER2-positive trastuzumab- refractory advanced esophagogastric cancer EGFR mutation-positive NSCLC and disease progression following prior clinical benefit on erlotinib Advanced solid tumors Advanced solid tumors Advanced solid tumors Afatinib plus NCT00950742 I trastuzumab (HER2 antibody) Afatinib plus NCT01649271 I trastuzumab (3 weekly) Neoadjuvant afatinib NCT01594177 II plus trastuzumab Afatinib plus NCT01522768 II trastuzumab Immunotherapy Afatinib plus NCT02364609 pembrolizumab (PD1 inhibitor) Chemotherapy Afatinib plus docetaxel NCT02171741 I Pulsatile afatinib plus NCT02171676 I docetaxel Afatinib plus paclitaxel NCT00809133 I AE: Adverse event; CR: Complete response; CRC: Colorectal cancer; HNSSC: Squamous cell carcinoma of the head and neck; HPV: Human papillomavirus; MTD: Maximum tolerated dose; NA: Not applicable; NR: Not reported; NSCLC: Non-small-cell lung cancer; OPSCC: Oropharyngeal squamous cell carcinoma; OR: Overall response; PR:Partial response; SD: Stable disease.
This relative uncertainty increases rapidly for small optical depths  (Young et al. , 2013)   nighttime for optical depths typically larger than 0. 3. For consistency, optical depths reported in the CALIOP 5 km cloud layer product are derived from the measured apparent two-way transmittance using Eq. (  2 ) only when the constrained technique is applied to retrieve the extinction profiles reported in the CALIOP cloud profile product. Otherwise, the optical depths reported in the version 3 layer product are retrieved using an initial lidar ratio set to S cal = 25 sr. Nevertheless, whenever the layer apparent two-way transmittance could be measured it is also reported, so that optical depth can also be computed a posteriori using Eq. (  2 ), as for the constrained retrievals, hence extending the data set of measured apparent optical depths.
, 2005)  and ancillary atmospheric and surface data from the GEOS 5 model of the Global Modeling and Assimilation Office  (Rienecker et al. , 2008). This second ensemble of cloud layers is called "type 2 clouds". Type 1 and type 2 clouds will be evaluated separately as their sources of uncertainty are different. Indeed, for type 1 clouds, R BG is derived purely from observations and is expected to be unbiased with respect to measured radiances. A random error dT BG is assumed, which is arbitrarily augmented from the instrumental random noise dT m = ±0. 3 to ±0. 5 K to account for possible differences between the studied area and the nearby non-cloudy area. The blackbody radiance R BB is computed from the FAS-RAD model and the thermodynamic temperature, T c , at the centroid altitude, Z c , of the CALIOP attenuated backscatter profile at 532 nm within the cloud layer  (Vaughan et al.
As the intent is to evaluate IIR retrievals, analyses are conducted for single-layered semi-transparent cirrus clouds over ocean. Data selection is further restricted to the subset of cirrus clouds composed of randomly oriented ice crystals for which the ice-water phase classification is reported with high confidence. In addition, possible contamination from mixed-phase clouds is minimized by restricting the analysis to clouds whose temperature at base altitude is colder than -20 • C  (Hu et al. , 2010). CALIOP optical depths and extinction profiles are retrieved from the constrained technique described previously. The chosen time period covers 12 months in 2008. Each cloud is composed of a number, n, of vertical bins, i, of resolution δz, with i = 1 to i = n extending from base to top. Emissivity in bin i is noted ε(i) and absorption optical depth derived from Eq.