dataesr/scientific-paragraphs-categorization huggingface dataset:
Phylogenetic analyses of Wolbachia endosymbionts Sequences generated during the present study and previously published from draft/complete genomes were aligned for each gene using SATe-II  (Liu et al. , 2012)  and subsequently concatenated. The complete dataset comprised 53 Wolbachia genotypes and had a length of 2480 bp. For each gene, the best-fitting substitution model was determined using the corrected version of the Akaike Information Criterion (AICc), JMo-delTest analyses (v2. 1. 10)  (Guindon and Gascuel, 2003). HKY+I was the best fit for ftsZ; HKY+I+Γ for 16S rDNA; K81uf+Γ for dnaA; TMP3uf for coxA; and TMP3uf+Γ for fbpA and gatB. The phylogenetic relationships of the Wolbachia genotypes based on the concatenation of these six genes were inferred by the maximum-likelihood method using RaxML-ng  (Kozlov et al.
, 2019). The dataset was partitioned to implement the best-fitting substitution model for each gene. The program was executed by generating 10 random start trees by using 1000 bootstrap replicates. (Mullin & Orihel, 1972)   Eberhard & Orihel, 1984 3. 1. 1. Taxonomic   Voucher material deposited: One female (MNHN-IN-110YT: UG2 from Ulu Gombak, Selangor) and one male (MNHN-IN-111YT: UG4 from Ulu Gombak, Selangor) were deposited in the Museum National d'Histoire Naturelle (MNHN), Paris, France. Additional specimens (7 females, MdF-1-7; 3 males, MdM-1-3) were deposited in the Museum of Zoology, Institute of Biological Sciences, Universiti Malaya.
Redescription of Mansonella (Tupainema) dunni Site in host: Adult worms occurred in the subcutaneous connective tissues of the neck and abdomen and microfilariae circulated in the blood of the common treeshrews. Representative DNA sequences: All sequence data generated were deposited in the GenBank database. Sequence data for M. (Tup. ) dunni (F1): cox1 (OR198850), 12S rDNA (OR210206), 18S rDNA (OR198492), MyoHC (OR555759), hsp70 (OR555767), rbp1 (OR555760) and 28S rDNA (OR206512) (Supplementary Table  S1 ). Additional sequence data for specimens (M1-M2; G3-G4) of M. (Tup. ) dunni: M1: cox1 (KY434306), 12S rDNA (KY434310); M2: cox1 (KY434307), 12S rDNA (KY434311); M2 C1: ITS1 (KY434312); M2 C2: ITS1 (KY434313); M2 C3: ITS1 (KY434314); G3: cox1 (KY434308); and G4: cox1 (KY434309). Sequence data for the Wolbachia endosymbionts of M.
(M. ) ozzardi and pointed bosses in M. (Tup. ) dunni  (Orihel and Eberhard, 1982; Eberhard and Orihel, 1984; Bain et al. , 2015). The microfilariae of M. (Tup. ) dunni and M. (M. ) ozzardi are remarkably similar in that the tip of the tail is without a nucleus or nuclei. In contrast, species of the subgenera Tetrapetalonema, Esslingeria and Cutifilaria have microfilariae with nuclei Fig. 4. Phylogenetic tree of Wolbachia endosymbionts based on six markers using maximum-likelihood inference. Analysis based on concatenation of 16S rDNA, ftsZ, dnaA, coxA, fbpA and gatB. The dataset was partitioned to implement the best-fitting substitution model for each gene. The robustness of nodes was assessed with 1000 bootstrap replicates. The Wolbachia supergroups (A-F, H and J) were identified according to  Lefoulon et al.
Acknowledgements We are grateful to  Academician Dr Yong Hoi Sen , Senior Fellow of the  Academy of Science Malaysia  and  Professor Emeritus  of the  Universiti Malaya , who warmly encouraged us in our research efforts. We thank  Drs Mohd Sofian Azirun  and  Rosli Hashim , Professors of the  Universiti Malaya , who conducted the  Scientific Inventory in Ulu Gombak Field Studies Centre, Universiti Malaya, Selangor.
Data availability All newly generated gene sequences of M. (Tup. ) dunni (F1) were deposited in the GenBank database under the following accession numbers: OR198850 (cox1), OR210206 (12S rDNA), OR198492 (18S rDNA), OR555759 (MyoHC), OR555767 (hsp70), OR555760 (rbp1) and OR206512 (28S rDNA). Additional sequence data for specimens (M1-M2; G3-G4) of M. (Tup. ) dunni: M1: KY434306 (cox1), KY434310 (12S rDNA); M2: KY434307 (cox1), KY434311 (12S rDNA); M2 C1: KY434312 (ITS1); M2 C2: KY434313 (ITS1); M2 C3: KY434314 (ITS1); G3: KY434308 (cox1); and G4: KY434309 (cox1). Sequence data for the Wolbachia endosymbionts of M. (Tup. ) dunni: M1: OR555761 (dnaA), OR555763 (ftsZ) and OR555765 (gatB); M2: OR555762 (dnaA), OR555764 (ftsZ) and OR555766 (gatB). Voucher specimens are deposited in the Museum National d'Histoire Naturelle (MNHN), Paris, France, under accession numbers MNHN-IN-110YT for the female of M.
Feature variance was then calculated based on the standardized values. Finally, we selected features which were repeatedly variable across datasets for integration via function SelectIntegrationFeatures. We then identified anchors using the FindIntegrationAnchors() function, which takes a list of Seurat objects as input, and use these anchors to integrate different datasets together via the IntegrateData function (44). Dimensionality reduction to identify anchors was performed using reciprocal principal component analysis.
METHODS This retrospective study is from the Acute Leukemia Working Party (ALWP) of the European Society for Blood and Marrow Transplantation (EBMT), a working group of more than 600 transplant centers, mostly located in Europe, that are required to report annually all consecutive transplantations and follow-up data. Data are entered, managed, and maintained in a central database with internet access; each EBMT center is represented in this database. There are no restrictions on centers for reporting data, except those required by law on patient consent and data confidentiality and accuracy. Quality control measures include several independent systems: confirmation of validity of the entered data by the reporting team, selective comparison of the survey data with MED-A data sets in the EBMT registry database, cross-checking with the National Registries, and regular in-house and external data audits.
Therefore, owing to its radiomimetic properties and its ability to cross the blood-brain barrier, several centers use thiotepa as an alternative to TBI in both the MAC and RIC settings for allo-HSCT in ALL  [6, 16]. Although Eder et al. [6]  showed that the use of thiotepa-based MAC regimens is associated with inferior transplantation outcomes compared to TBI-based MAC regimens, no comparative analysis of the 2 RIC regimens has been reported to date  [6]. Therefore, we used data from the EBMT registry to explore this issue. Interestingly, we observed no differences in any transplantation outcome when using thiotepa or TBI at 4 to 6 Gy, highlighting that both strategies may represent a valid option when choosing the conditioning regimen for the elderly or for patients with comorbidities considered not eligible for MAC.
ACKNOWLEDGMENTS The authors thank  Emmanuelle Polge  from the office of the ALWP of the EBMT, the clinical staff and investigators involved in this research, and especially the patients who took part. Financial disclosure: There is no financial disclosure to report for this study Conflict of interest statement: There are no conflicts of interest to report. Authorship statement: G. B. designed the study and wrote the manuscript, M. L. performed the statistical analysis, M. L. , A. N. , and M. M. revised the manuscript, and all the authors reviewed its final version. S. M. , A. R. , Z. N. O. , J. H. B. , W. R. , I. Y. A. , G. G. , J. S. , W. A. , Y. N. , N. F. , and S. G. were the principal investigators at the centers recruiting the highest number of patients into the study.
[ 5 ]  Recent studies from England and Wales investigated the demographics, outcomes, and trends of admission in patients with SAE in critical care units between 2002 and 2011, and demonstrated that it represents a modest burden of work with a high survival rate in ICUs. [ 6 ]  Another cohort in Australia, spanning from 1996 to 2003, showed a reduction in the proportion of ICU admissions for SAE, and reduced mortality. [ 7 , 8 ]  Noninvasive mechanical ventilation (NIV) use for SAE seems to be increasing, and few data exist regarding the use of IMV in this population. [ 5 , 9 ]  The aim of the current retrospective study was to investigate patient characteristics, ICU management, and outcomes of adult SAE admissions in 40 ICUs in the greater Paris area from the Collège des Utilisateurs de Bases de données en Réanimation (CUB-REA) network  [ 10 ]  over a 20-year period.
Study and patients The CUB-REA network was used, which prospectively collects data from all patients admitted to 40 ICUs in the greater Paris area, as described previously. [ 11 ]  Participating centers are listed in the supplementary material online (Appendix S1). All adult admissions for SAE from January 1, 1997, to December 31, 2016, were included. Only patients with a primary or secondary diagnosis of SAE were included. Admissions with an associated chronic obstructive pulmonary disease (COPD) diagnosis were excluded.
[ 34 ]  If mortality associated with SAE remains stable despite more severe illness, it is imperative that clinicians treating such patients have a clear understanding of how gas trapping can occur, and of how it may be recognized, measured, and limited. The major strength of the present study is the large size of the population included in the CUB-Réa network, with good reliability of data pertaining to stays, illness severity, and workload that facilitated detailed evaluation of changes over two decades. [ 10 ]  Notably, however, a lack of reproducibility of diagnosis coding in the CUB-Réa network, the retrospective design of this study, and the restraints of the database constitute study limitations. The parameters of mechanical ventilation were not recorded, and neither were details on the timing of ventilation, the sequence of ventilation modalities, or the use of medical therapy.
Pre-admission data such as maintenance therapy, parameters of gas exchange, body mass index, and smoker status were also not mentioned in the database. Throughout the two-decade study period, the need for catecholamine decreased -almost disappearing from 2005 -and outcomes of severe asthma improved, with fewer deaths, suggesting better management of hyperinflation. Notably, however, a lack of tracking negated clear identification of a possible association between progress in mechanical ventilation techniques and improved hyperinflation management, and mortality rates related to other interventions such as ECLS were not recorded. ECLS was seldom used during the 20-year study period, and the type of extracorporeal membrane oxygenation, whether it was veno-venous or veno-arterial, was not specified.
Contractility analysis Tissues started contracting less than 24 hours after seeding, which was visible through the deformation of their central pillar (Supplemental video 1). Each tissue was recorded in brightfield imaging, at a 10X magnification with a high-speed camera (Supplemental video 1). An in-house Matlab code was developed to quantify the contraction and relaxation phases of the tissues by monitoring the area of the central pillar over time (Figure  3A ). The beat rate of the tissues first decreased between day 1 and day 3 and increased again to reach 0. 58±0. 030 Hz on day 14 (Figure  3B ). The contraction stress developed by the tissues increased from day 1 until day 7 (Figure  3C ). At day 7, the contractility parameters stabilized with an average stress of 1. 4±0. 1 mN/mm 2 (Figure  3C.
Tissues recording and analysis The cardiac rings were recorded for 10 seconds in brightfield imaging with a high speed CCD camera (PL-D672MU, Pixelink) mounted on a microscope (Primovert, Zeiss), at a 10X magnification. The videos were then analyzed with a custom Matlab script. Briefly, the area of the central pillar is monitored in time and allows to recover the contraction amplitude in time Amplitude(t)= Max(Area)-Area(t) and therefore the contraction strain in time (in terms of area) 𝜖 𝐴 calculated as 𝜖 𝐴 (𝑡) = (𝑀𝑎𝑥(𝐴𝑟𝑒𝑎) -𝐴𝑟𝑒𝑎(𝑡))∕𝑀𝑎𝑥(𝐴𝑟𝑒𝑎) as well as the derivative of this strain in time. 𝜖 𝐴 (𝑡) is linked to the linear strain 𝜖 with the formula 𝜖 = Δ𝑟 𝑟 𝑚𝑎𝑥 = 𝜖 𝐴 1+ √ 1-𝜖 𝐴. As we measured the Young's Modulus of the gel, we can recover the stress developed by the cardiac rings 𝜎 = 𝐸.
Acknowledgments We thank the  iPS core facility of Paris Cardiovascular Research Center  for its support for cell culture. We thank  Camille Knops  and  Yunling Xu  from the  Flow Cytometry  and the Microscopy platforms, respectively, from  Université de Paris, Paris Cardiovascular Research Center, Paris, France. Schemes were created with BioRender. com (access date:10/03/2023).
X-ray micro-CT analysis After sacrifice, WT, Hyp, and HLA-B27 transgenic mice were scanned by using an in vivo high-resolution X-ray micro-CT instrument (Quantum FX Caliper, Life Sciences, Perkin Elmer, Waltham, MA, USA) hosted by the life Imaging Facility (Plateforme des Imageries du Vivant, URP2496, Montrouge, France). Standard acquisition settings were applied (voltage 90 kV and intensity 160 mA), and 3D scans were performed with field of view 5 mm, alternatively focused on both right and left SIJs and on the distal metaphysis of the left femur (both with scan time 180 s and voxel size 10 μm 3 ). Micro-CT datasets were analyzed by using the built-in multiplanar reconstruction tool Osirix 5. 8 (Pixmeo, Switzerland) to obtain a time series of images aligned anatomically for each region for each animal.
Axial and coronal images of the SIJ and femur were reconstructed. The architectural analysis was performed according to the good practice recommendations published by Bouxsein et al. [3]. The trabecular bone was analyzed at the SIJ and the distal metaphysis of the left femur. Regarding the trabecular analysis, at the left femur, first, image stacks were oriented in the same direction by using Dataviewer software (Skyscan 1. 5. 2. 4; Kontich, Belgium) to determine the region of interest (ROI). The starting point used as reference for the ROI definition was located at the most proximal point of the growth plate (Supplementary Fig. 1A ). Second, quantification of the distal metaphysis bone microarchitecture below the growth plate involved using CT-Analyzer software (Skyscan 1. 13. 5. 1) (Supplementary Fig.
43 mm). We obtained 200 slices for each ROI (distal metaphysis of femur for trabecular bone) corresponding to 2 mm, which is equal to 12. 9 % of the total femur length (2 mm / 15. 47 mm × 100 = 12. 9 %). Consequently, the ROIs for each femur were adjusted according to this calculation to obtain 12. 9 % of the total femur length. Regarding the trabecular analysis of SIJ, first, image stacks were oriented in the same direction by using Dataviewer software to determine the ROIs (Supplementary Fig. 1D-E ). From the initial micro-CT datasets, we selected 200 slices starting from the lower part of the joint (Supplementary Fig. 1C-E ). Second, the bone microarchitecture was quantified separately on the sacral and iliac bone by using CT-Analyzer software (Skyscan 1. 13. 5. 1). An ROI was drawn in the transverse sections along the cortical zone.
Batch processing involved using a median filter (with radius 1) for noise reduction, and adaptive thresholding was performed with a radius of 1. After segmentation, batch processing was used to calculate the same 3D parameters of the binary image as described above. Cortical bone analyses were performed in the articular sacroiliac space of SIJs with the 200 slices from the lower part of the SIJ. Quantification was performed separately on the sacral and iliac cortical bone by using CT-Analyzer software (Skyscan 1. 13. 5. 1). Then by an exclusion selection, we selected the articular cortex of the sacral slope or the iliac slope (Supplementary Fig. 1F ). Batch processing involved using a median filter (with radius 1) for noise reduction, and adaptive thresholding was performed with a radius of 1.
Histological quantification Histological quantification of trabecular bone surface and osteocyte density were performed on representative sections of iliac bone and distal femur from 6-month-old WT mice (n = 4 per group) stained by Trichrome de Lillie-Safranin O. The ROI was focused on the secondary spongiosa (Supplementary Fig. 7 A-B ). Images were processed using Fiji (Fiji Is Just ImageJ) software 2. 1. 0/1. 53q, version for Mac. Each ROI was split in square fields. The Bone Surface/Total Surface ratio (BS/TS) was determined by calculating the trabecular surface relative to the total surface of the area of interest on three sections per mouse. Osteocyte nuclei were counted twice by two independent observers (SH and KI) on each square field. The number of osteocytes was then reported relative to the trabecular surface.
Acknowledgments We are grateful to  Coralie Torrens  and  Brigitte Baroukh  for their kind assistance with the histological techniques and  Jérémy Sadoine  for his assistance with micro-CT analyses; in vivo imaging was performed at the  Life Imaging Facility of Université Paris Cité (Plateforme d'Imagerie du Vivant (PIV)) , supported by  France Life Imaging  (grant  ANR-11-INBS-0006 ) and  Infrastructures Biologie-Santé , and  DIM Thérapie Génique.
6  Finally, previous changes in the definitions of tubular atrophy, t, and t-IFTA have led to confusion and likely inconsistent application of the definition of caTCMR, even among specialists. The definitions of these lesions were clarified and agreed upon (reported in the Banff 2022 Kidney Meeting Report). 1  In summary, current evidence converges to suggest that i-IFTA is nonspecific both in its clinical associations and its molecular profile, but that it has a poor prognosis, even at a low i-IFTA ¼ 1 score, and worse than fibrosis without inflammation. However, further data are needed to provide evidence that the Banff Classification thresholds for caTCMR (including t and ti thresholds in addition to i-IFTA) guarantee an increased diagnostic specificity for a T cell-mediated rejection process.
Digital transplant pathology and machine learning Several sessions in the Banff 2022 meeting reviewed advances in the field of machine learning applied to digital pathology. The current work of the Banff Digital Pathology Working Group is the subject of 2 publications 27 (Farris et al, under review), and future plans are outlined in Supplementary Table  S10. A growing number of kidney transplant pathologists are using digital pathology for their daily diagnostic practice, research, and clinical trials, facilitating accessibility, and sharing of digitized whole slide images (WSI), without apparent quality loss. 28  Moreover, many are starting to curate datasets of WSI with or without annotations that can be used to train models to perform diagnostic tasks. Potential deep learning-derived decision-support systems in kidney transplant pathology include applications that deliver segmentation of microanatomical structures (eg, glomeruli  29  ), high-throughput morphometric quantification (eg, tubular diameters  30  ), object detection (eg, inflammatory cells  31, 32  ), and weakly supervised slide-level classification (eg, rejection versus nonrejection to prioritize workload), with or without computer-assisted diagnosis overlays to WSI that guide the nephropathologist toward biopsy zones with highly informative features.
33  Also, the evaluation of difficult lesions like transplant glomerulopathy could be improved with prognostic implications, as recently demonstrated. 34  It has been shown that digital features significantly correlate with Banff Lesion Scores, but are also more sensitive to subtle pathological changes, below the thresholds in the Banff grading system. 35  Composite damage scores calculated from those digital features outperformed Banff scores with superior graft loss prediction accuracy, indicating the potential of these models in addition to or beyond the Banff scoring system, eg, also when applied to time zero biopsies. 35  A major bottleneck in developing deep learning models remains the access to large datasets of WSI annotated both for their pathology features and clinical features including outcomes.
EMA qualified the iBox Scoring System as a secondary endpoint prognostic for death-censored allograft loss in kidney transplant recipients, to be used in clinical trials to support the evaluation of novel immunosuppressive therapy applications. 55  In this specific context of use, the c-statistics for the derivation dataset were 0. 809 (0. 01 standard error) for the Full (with biopsy) and 0. 803 (0. 01 standard error) for the abbreviated (without biopsy) iBox Scoring System. Full iBox Scoring System (with biopsy), has an Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) of 0. 85 (0. 02 standard error), while the Abbreviated iBox Scoring System (without biopsy) reaches a ROC AUC of 0. 84 (0. 02 standard error). Although EMA did not qualify the iBox Scoring System as a surrogate endpoint, EMA encourages further development of the scoring system targeting potential future qualification as a surrogate endpoint.
Conclusions As indicated in a recent review, over the past 30 years, the Banff Classification for Renal Allograft Pathology 18 has shown agility in adapting to advancing pathophysiological insights, changing clinical and regulatory contexts, and new diagnostic techniques. This agility remains vital. An integrated consensus process is followed to avoid overly frequent and minor changes to the classification and consequent difficulties in following the Banff rules in routine clinical care and in clinical trials. 1  In this paper, we outlined the existing knowledge gaps with a view to stimulating efforts by the international transplant community to generate the respective data needed to find answers to key unanswered questions. Progress will be addressed at the next Banff 2024 meeting, which will be held in Paris, France, September 16-20, 2024.
A first version of this multi-lumen perfusion system was planned to be evaluated in a prospective study registered in 2015 (ClinicalTrials. gov, NCT02633124)  [19] , but the study was stopped in 2020 for technical reasons related to product availability. Since then, a modified version has been manufactured, including the addition of an Escape-line and two supplementary ports, allowing the administration of eight medications simultaneously, to better correspond to the needs of drug administration in the most severely ill neonates (Figure  1 ). The same central line insertion and maintenance procedures were used before and after implementation of the new perfusion system (Table  S1 , see online supplementary material). These concerned hand hygiene, barrier precautions, skin antisepsis, dressing assessment and change, replacement of administration sets, and catheter hub disinfection.
New perfusion system Five lumens: Four lumens connected to ports 1-4 (green) and one central lumen tertiary care centre. Data were collected about moderate or severe bronchopulmonary dysplasia (BPD; ventilatory support or oxygen therapy at 36 weeks), patent ductus arteriosus (PDA), grade 3 intraventricular haemorrhage (IVH), periventricular leukomalacia (PVL), stage 2 retinopathy of prematurity (ROP) and grade 2 necrotizing enterocolitis (NEC). Severe morbidity was defined as the presence of at least one of the following: surgical PDA, stage 2 ROP, grade 2 NEC, moderate or severe BPD, grade 3 IVH or PVL. Anthropometric data were collected at birth and at 36 weeks or discharge, whichever came first. Zscores were calculated, with infants considered to be small for gestational age when the z-score for body weight was -1.
001; Table  IV ). Since the duration of parenteral nutrition and duration of central line use are highly correlated (r>0. 9 in study dataset), both variables cannot be entered into the multi-variate model simultaneously, so the authors decided to enter duration of central line use alone. All VIF scores were close to 1 (1. 21 for period, 1. 14 for gestational age, 1. 02 for small for gestational age, 1. 36 for duration of central line use), suggesting the absence of multi-collinearity.