dataesr/scientific-paragraphs-categorization huggingface dataset:
-Second, the choice of the dosing software and the PK models is a key determinant for antimicrobial MIPD-guided optimization success. The PK/PD dosing software used in the DOLPHIN trial-InsightRx ® -although registered as a CE-labeled medical device with published embedded PK models, failed to predict adequate BL and ciprofloxacin doses in ICU patients. As previously reported, the external evaluation of published population PK models may lead to poor predictive performance when applying to a cohort of ICU patients different from the one used to develop the PK models as shown for meropenem  [71, 72]. Thus, it is necessary to perform a fit-for-purpose evaluation of the models to assess their predictive performance in the MIPD setting they are intended to be used before any implementation. -Third, only 61% of patients in the MIPD group had a second TDM sampling.
Barriers to the Widespread Use of Dosing Software That Need to Be Overcome Before MIPD becomes common clinical reality, several issues must be addressed  [73]. -First, in the near future, the regulatory framework for antimicrobial dosing software tools needs to be reinforced. Software developers may be required to register their dosing software with relevant regulatory bodies before health services are able to incorporate the technology. -Second, the difficulty of MIPD use for untrained healthcare providers questions the integration of specialized pharmacists or pharmacologists into clinical teams. Indeed, to drive adoption of these tools in clinical practice, it is essential to provide proper education of the intended end-user. The lack of dedicated time for practitioners to use these tools on a larger scale together with a lack of knowledge about the reliability of software outputs, as well as understanding of how the software works, have been identified as influencing trust in dose-prediction software  [74].
Implementation of MIPD into dosing advisory service deserves consideration to facilitate translation of Bayesian forecasting dosing recommendations into clinical practice as already demonstrated for vancomycin  [74]. -Third, the ability to integrate dose-prediction software within existing hospital electronic medication management systems helps minimizing the need for prescribers to input data and is a key aspect considered by prescribers when deciding to accept software. Providing clinicians with quality-assured user-friendly decision support tools available in application form for personal mobile devices, integrated into electronic hospital record (EHR) prescribing software, is of paramount importance for the widespread implementation of MIPD. -Fourth, cost-effectiveness of using BL dosing software must be demonstrated.
Precision dosing may require additional costs initially for analysis of drug concentration or other biomarkers that provide information necessary for optimal dose selection. These analyses, though theoretically cost-effective, may require a learning curve for clinicians before expenditures are reduced in clinical practice. Another cost associated with precision dosing is the integration of drug dosing software into EHRs. Although favorable cost outcomes from using dosing software for non-BL antibiotics have been reported, the DOLPHIN trial found incremental costs of EUR 5312 with an average decrease in 6 months QALY of 0. 03 (range -0. 5 to 0. 5) in MIPD compared to the standard dosing  [69, 75].
Renal failure leads to a risk of toxicity by overdosing, proving the interest of anticipating increasing serum concentrations  [47]. Although there is extremely high variability of BL exposure in patients with renal failure or those undergoing RRT supports TDM and dose individualization, few studies have investigated whether TDM and subsequent dose adjustment could reduce such variability and improve BL exposure  [79]. To date, no randomized study assessing TDM interventions in patients undergoing RRT has been conducted, and the optimal dose adjustment approach (empirical dosing, nomograms or dosing software) remains to be determined. MIPD dosing and innovative approaches such as the integrated dialysis pharmacometrics model that incorporates all RRT samples (pre-and post-filter plasma and effluent), RRT types and settings and drug physiochemical properties to provide quantitative insight into drug clearance in patients receiving RRT should be considered in future studies  [80].
However, as weak correlations between measured CrCl and BL plasma concentrations and between measured CrCl and BL clearances were observed in this study, dosing adjustments based on measured CrCl only are unlikely to achieve PK/PD targets. Under these circumstances, TDM should be strongly encouraged to guide BL drug dosing as off-label dosing is often necessary to achieve therapeutic concentrations. Interestingly, the package insert of recently released antibiotics integrates ARC dosing recommendations, as seen for cefiderocol. MIPD may also be valuable in this population but has not been investigated yet. Post hoc analyses of the DOLPHIN trial are currently underway in such population and may inform future trials. Finally, another challenging situation for BL dosing optimization is infection with less susceptible pathogens requiring higher BL exposure to achieve PK/PD targets.
Future Perspectives Further well-designed prospective clinical trials will be required to determine the benefit of precision dosing and will be crucial to put the effort of TDM into cost effectiveness. In the near future, a multicenter randomized controlled superiority trial aiming to assess the effectiveness and safety of data driven automated antimicrobial dosing advice and a study combining the use of a Bayesian model with rapid molecular diagnostic test in order to offer an optimal personalized care will provide new insights into optimized TDM and MIPD benefit  [84, 85]. Artificial intelligence (AI) embedded into dosing software is a promising strategy  [86]. AI software uses reinforcement learning to provide recommendations on dose adaptation. AI software analyzes large patient databases to determine interventions that may influence patient outcome.
Conclusions Beta-lactam dosing optimization is a cornerstone of critically ill patient management. Therapeutic drug monitoring of BL antibiotics and the ability to individualize dosing regimens remains a promising approach with great potential to impact selective patient populations at high risk of inadequate BL exposure. For several reasons, current studies evaluating BL dosing optimization fail to demonstrate a decline in mortality. The combination of Beta-lactam dosing optimization with rapid molecular diagnostic testing to offer an optimal personalized care could be an interesting approach when designing further studies. The benefit of MIPD remains to be determined from safety and cost point of views. In the meantime, efforts must be pursued on an available, simple-to-operate and cost-effective TDM program that provides a short turnaround time in combination with reliable and easy-to-interpret results in the critical care setting.
This point was also highlighted in Giannopoulou et al. [54] , where the flows past an elliptical and a triangular cylinder were simulated with a particle vortex method (named Diffused Vortex Hydrodynamics or DVH) and compared with a Finite Volume Method (FVM). In  [54]  the simulations were carried out in unbounded domains only, whereas in the present work we consider confined domains. For this reason, the values of the drag and lift coefficients computed in  [54]  are slightly different than the same results discussed in the present work. Similarly to Giannopoulou et al. [54] , in the present work an FVM algorithm is also used for comparisons. The FVM numerical code used in the present work is a thoroughly validated solver named Xnavis and it adopts multi block, body-fitted structured grids that may be eventually overlapped.
2. In principle, different parts of the spiral have different pattern speeds if driven by a companion on an eccentric orbit. However, our data do not permit a radius-dependent assessment, and a single-value pattern speed is measured as a compromise. The speed of the pattern motion for spiral arm S1 is 0 •. 88 ±0 •. 07 yr -1 in the counterclockwise direction, assuming the companion-driven scenario that the pattern speed is a constant for S1. The uncertainty estimation is described in Appendix D. The deprojection will affect the spiral location determination, and subsequently the spiral motion measurement. However, the disk flaring of HD 100453 only has limited impact on the velocity of the spiral motion (see Appendix E). Throughout the paper we present the velocity of the spiral motion based on the best-fit model (h = 0.
Then the pipeline generated calibrated and roughly aligned (offsets<1 pix) data cube for each observation. In the K1 band, our DIsNMF approach can successfully model and then remove the thermal background. However, we did not cleanly remove all the thermal background emissions in K2 because of the stronger background variation at longer wavelengths (i. e. , K2) and limited calibration images in the SPHERE archive for modeling. To avoid potential influence from the residual of the background in K2, we only use K1 data to measure the spiral motion in this work.
Acknowledgements. We thank  Dr. Faustine Cantalloube  for the beneficial discussion about the low wind effect. The disk images of HD 100453 are based on observations collected at the  European Organisation for Astronomical Research in the Southern Hemisphere  under  ESO  programmes  095. C-0389 (A) and  0103. C-0847 (A). We thank all the principal investigators and their collaborators who prepared and performed the observations with SPHERE. Without their efforts, we would not be able to build the master reference library to enable our RDI technique. B. B. R. acknowledges funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant PROTOPLANETS No. 101002188 ), and from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement No.
101103114. R. D. acknowledges financial support provided by the  Natural Sciences and Engineering Research Council of Canada  through a  Discovery Grant , as well as the  Alfred P. Sloan Foundation  through a  Sloan Research Fellowship. E. C. acknowledges funding from the  European Research Council (ERC)  under the European Union's  Horizon Europe research and innovation programme (ESCAPE , grant agreement No  101044152 ). A. V. acknowledges funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No. 757561 ). J. -F. G. acknowledges funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement No  823823  (DUSTBUSTERS) and from the  ANR (Agence Nationale de la Recherche) of France  under contract number  ANR-16-CE31-0013  ( Planet-Forming-Disks ), and thanks the  LABEX Lyon Institute of Origins  ( ANR-10-LABX-0066 ) for its financial support within the  Plan France 2030  of the French government operated by the  ANR.
In 2019, a new underwater volcano was discovered at 3500 m below sea level (b. s. l. ), 50 km east of Mayotte Island in the northern part of the Mozambique Channel. In January 2021, the submarine eruption was still going on and the volcanic activity, along with the intense seismicity that accompanies this crisis, was monitored by the recently created REVOSIMA (MAyotte VOlcano and Seismic Monitoring) network. In this framework, four hydrophones were moored in the SOFAR channel in October 2020. Surrounding the volcano, they monitor sounds generated by the volcanic activity and the lava flows. The first year of hydroacoustic data evidenced many earthquakes, underwater landslides, large marine mammal calls, along with anthropogenic noise. Of particular interest are impulsive.
, 2022]. From multichannel seismic reflection profiles,  Malod et al. [1991]  identified N130°E trending structures within the Comoros Basin that are parallel to the movement of Madagascar with respect to the African Plate. These structures are compatible with linear features highlighted in recently re-processed gravity data and orthogonal to the regional magnetic anomalies  [Phethean et al. , 2016]. From newly acquired marine geophysical datasets,  Thinon et al. [2022]  show that the recent volcanic and tectonic deformation fits with the fossil oceanic crustal fabric in the western part of the Comoros Archipelago. It is also consistent either with a current regional transpression along an immature and dextral Somalia-Lwandle plate boundary  [Famin et al. , 2020]  or a transtension in between the East African rifts and Malagasy graben  [Feuillet et al.
MAHY11, MAHY12, and MAHY14 stopped recording, 22, 36, and 6 days before their recovery, respectively (see Supplementary Materials S1 and S2 for all spectrograms). MAHY11 failure was due to battery problems while that of MAHY12 is not yet understood. As for MAHY14, the failure is related to a SD card problem and recovery of the data might still be possible. The next maintenance of the AuHs is scheduled for Summer 2022. Various types of sounds were highlighted in the data, including marine mammal calls, anthropogenic noise  [Figures 2 and 3; Bazin et al. , 2021] , but only those related to the ongoing submarine volcanic   [Feuillet, 2019 , Feuillet et al. , 2021]  and SHOM  [2016]. activity are reported here. The data are obscured by seismic shots from three exploration surveys that took place in the Mozambique Channel: from 27/12/2020 to 04/02/2021 (SISMAORE  [Thinon et al.
A daily average of 13 and 11 impulsive events was observed in January 2021 and February 2021, respectively, with a daily occurrence varying between 0 and 47 events (Table  1 , Figure  6 ). We also tested a simple automatic detector tuned for these impulsive events based on the amplitude variations in the spectrograms of the four AuHs. The threshold levels (minimum amplitude level in the spectrum, minimum amplitude drop, maximum event duration, etc) were adjusted by fitting the previously handpicked detections during mid-November 2020 on the MAHY04 dataset. Daily automatic detections for the four AuHs is presented in Figure  7. The automatic detections led to the identification of more impulsive events than the events picked manually due to false detections related to the high noise level in the data (i.
Localization of hydroacoustic activity From a visual inspection of the days with a high SNR on the four AuH datasets (those with good detections of impulsive events), 15/11/2020 appears as one of the most active days. Hence, we focussed our analysis on this specific date. Hand picking the impulsive events on this day resulted in a catalog of 81 events containing information on their latitude, longitude, SL and uncertainties. In fact, there were more impulsive events detected by the AuHs during that day, especially by MAHY04, but only 81 of them were clearly recorded simultaneously by the four AuHs. The picking uncertainty is on the order of 6 s. The mean error on the positions is 1654 m while the mean error in origin time of the source is 0. 87 s. All the events identified on 15/11/2020 are located in the Tiktak area of the new lava flow field that was emplaced between May 2020 and January 2021.
History and morphological evolution of the Tiktak flow field To examine the relationships between the temporal and spatial distribution of the impulsive events and the lava flow field in the Tiktak region, we examined the available bathymetric data. Ship-borne multibeam echosounder data was acquired during three successive cruises (MAYOBS13-2, MAYOBS15 and MAYOBS17). The datasets were re-processed with the GLOBE software  [GLobal Oceanographic Bathymetry Explorer, Poncelet et al. , 2021]  to produce digital terrain models (30-m grid-cell spacing) and seafloor backscatter imagery. Successive surveys were compared to detect depth changes due to new lava deposits and to estimate their area and thickness (Figure  9 ). Assuming a vertical resolution of 5 m, new volcanic material can be inferred when depth changes exceed 10 m over a sufficiently large area.
The data show up to 60 m-thick new lava flow between May 2020 and October 2020 in the Tiktak area. It continued growing after October 2020, but had stopped growing by January 2021. The AuH array was deployed during the last months of activity of the Tiktak lava flows. The impulsive events detected on 15/11/2020 can be seen as a snapshot of the eruptive activity and we suggest that they highlight areas of active flow emplacement.
, 2022]. The occurrence of this seismic cluster only between 25 and 50 km depth is still unexplained. We suppose that a more detailed analysis possibly using template matching might reveal nonvolcanotectonic events in the so-called aseismic zone [e. g. Duputel et al. , 2019]. The available hydroacoustic data do not provide the reason for why the upward and southward migration of magma in the crust seem silent, nevertheless it can pinpoint the time windows where available OBS data could be further analyzed. Streaming real-time data to shore is not yet available and one can mitigate this problem by making frequent access to the hydroacoustic network, at short range from Mayotte. However, deploying and recovering the current AuH moorings requires vessels with an A-frame or a small crane, and a winch, which are not available in Mayotte.
Conclusions Although the hydrophones were deployed more than two years after the onset of the eruption, they were able to record numerous impulsive events in the vicinity of the NVE. The coincidence of the location of the impulsive events with the area of active lava flow emplacement supports the interpretation that they are directly related to lava-water interactions, and as such, monitoring these acoustic events provides a way to remotely detect and locate ongoing submarine eruptions. However, the automatic detection and location of such impulsive events needs to be improved before the scientific value of the full dataset can be revealed and these new methods can be used for risk assessment and monitoring. A new research and monitoring endeavor focussed on Mayotte has just started in France, with the MARMOR (Marine Advanced geophysical Research equipment and Mayotte multidisciplinary Observatory for Research and response) project funded by the 2021 PIA3-EQUIPEX plan.
Similar to the Ocean Observatories Initiative [OOI,  Kelley et al. , 2014]  that has streamed data live to shore since 2014 at Axial Seamount, MARMOR will finance a permanent cabled observatory to monitor the new Mayotte volcanic area with a network of multidisciplinary instruments deployed on the seafloor and in the water column, including hydrophones (HYDROBS type). These preliminary results show the potential value of hydroacoustic monitoring to better understand volcanic processes occurring on the seafloor during submarine eruptions.
Acknowledgments Since June 2019, all activities performed on Mayotte by the REVOSIMA (https://doi. org/10. 18715/mayotte. revosima)monitoring network are funded by  MESRI (Higher Education, Research and Innovation Ministry) ,  MTE (Environment Ministry)  and  MOM (Overseas Territory Ministry)  with the support from  MI (Interior Ministry) ,  MINARM (Armed Forces Ministry), DIRMOM (joint-government department for Major Hazards  in the Overseas). All marine operations are performed as part of the MAYOBS set of cruises (https://doi. org/10. 18142/291 )and we thank the captains and crews of the  R/V Marion Dufresne ,  R/V Pourquoi  Pas? and  BSAOM Champlain. We thank  W. Chadwick  and an anonymous reviewer for their very constructive comments on this publication. We express our gratitude to  M.
DNA substrates and incision assay All DNA oligonucleotides were ordered from MWG Biotech and their sequences are provided in Table  S3. Incision activity measurements were performed using duplexed 50 mer dsDNA oligonucleotides composed of a 5 -ATTO633-labelled strand containing a fluorescein conjugated thymine in position 26 (strand name: 5 -ATTO633-F26-seq1) annealed with an unlabelled complementary strand (strand name: Rev-seq1). As described previously  (45) , for the incision assay, 25 nM F26-seq1 dsDNA substrate was incubated at 37  C for 20 min followed by cooling on ice. New reactions were then prepared as described above for the F26-seq1 substrate. All reactions were then analyzed on 20% TBE-8 M urea acrylamide gels pre-run at 5 W/gel in 1× TBE buffer. The gels were run for 35 min and the DNA bands were visualized and quantified on a Chemidoc MP imager (Bio-Rad) using the appropriate excitation light and detection filters for the green and red fluorophores respectively and the ImageLab software (Bio-Rad).
DNA binding assays Equilibrium fluorescence polarization DNA binding assays were performed on a Clariostar (BMG Labtech) microplate reader, fitted with polarization filters. The DNA substrate consisted of 50 mer dsDNA containing a fluoresceinconjugated thymine in position 26, named 50mer-F26, obtained by annealing For-F26-seq1 with Rev-seq1 (Table  S3 ). 0 to 2 M UvrB, UvrC full-length and deletion constructs or UvrB/UvrC complex were titrated into 2 nM 50mer-F26 DNA in binding buffer composed of 50 mM Tris-HCl pH 7. 5, 50 mM KCl, 5 mM DTT, 0. 01% Tween 20, 2. 5 mM MgCl 2 supplemented with 0. 1 mg/ml BSA. When stated, 2. 5 mM ATP was also included in the reaction buffer. Reaction volumes were set to 50 l. In all cases, after subtracting the polarization values obtained for DNA alone, the mean data from at least three independent experiments were fitted to a standard binding equation (Y = B max *X h /(K d h + X h )) assuming a single binding site with Hill slope (h) using GraphPad Prism 8, where Y is the difference between the polarization of completely bound and completely free oligo, X is the protein concentration and K d is the equilibrium dissociation constant.
Crystallization, X-ray data collection, structure determination, homology modelling and structure prediction Crystals of UvrC-C were obtained by vapor diffusion, by mixing and equilibrating UvrC-C protein solution at a concentration of 20 mg/ml with a reservoir solution containing 24-26% PEG 5000 MME or PEG 3350 and 0. 1M Bis-Tris pH 6. 5. Crystals were cryoprotected in mother liquor supplemented with 20% glycerol and flash-frozen in liquid nitrogen. X-ray diffraction data were collected at 100 K on beamline ID14-EH4 at the European Synchrotron Radiation Facility (ESRF). Diffraction data were integrated using XDS  (49)  and scaled with SCALA  (50). All diffraction data were twinned, so Truncate  (50)  and Detwin  (51)  were used to estimate the twin fraction and detwin the data. A complete dataset was collected to 1.
80 Å. Phases were calculated by molecular replacement using Phaser (52), using the crystal structures of the C-terminal RNase H and Helix-hairpin-Helix (HhH) domains of T. maritima UvrC (TmUvrC) as search models (PDB: 2NRT; (26)). Models of both domains (residues 367-546 and 550-608 respectively) could be built using Coot  (53, 54)  and were refined using Refmac  (55). A summary of the data collection parameters and processing and refinement statistics is given in Table  1. Coordinates and structure factors have been deposited in the PDB (PDB: 8B0Q). A homology model of the N-terminal GIY-YIG endonuclease domain of D. radiodurans UvrC (UvrC-NEndo) was generated using SWISS-MODEL (56) and T. maritima UvrC-NEndo in its Mn-bound state (PDB: 1YD5) as a template. The UvrC-NEndo of D. radiodurans and T.