dataesr/scientific-paragraphs-categorization huggingface dataset:
plantarum genome assemblies [search date: 16. 7. 2021]. The median total length is 3,253,870 bp, with a median protein (CDS) count of 2926 and median GC% of 44. 5. Thus, the sequencing of IMI 507027 produced a complete genome (99. 4%) comparable in size to the median genomic parameters for this organism. The 16S rRNA analysis, performed using the RDP Sequence Match against type strains, gave the highest similarity score to L. plantarum and other lactic acid bacteria. The alignment-free genome distance estimation analysis with Mash using MinHash evidenced L. plantarum JDM1 (GenBank accession number: CP001617) as the closest genome. The alignment-based calculation of average nucleotide identity (ANI) gave a value of 99. 9926% between IMI 507027 and L. plantarum JDM1. The strain was unequivocally identified as L.
plantarum. Searches for antimicrobial resistance genes were made against different bacterial antimicrobial gene databases. According to European Food Safety Authority (EFSA) sequences with above 80% identity and 70% coverage should be considered for further analysis  [1]. No antimicrobial resistance genes exceeding these threshold values were found. Similarly, no genes encoding potential virulence or pathogenicity factors were identified. One contig (contig_22) was identified as a potential plasmid.
Taxonomic identification of the strain The following bioinformatics tools were used: SeqMatch v3 in RDP release 11. 6 (Ribosome Database Project)  [8]  for 16S rRNA analysis; Mash using MinHash v. 0. 1. 1  [9]  for alignment-free genome distance estimation, and OrthoANI v. 1. 40  [10]  for calculating average nucleotide identity.
Search for antimicrobial resistance genes and virulence factors The IMI 507027 genome was screened against two antimicrobial resistance gene databases; the NCBI Bacterial Antimicrobial Resistance Reference Gene database (NCBI PRJNA313047; database version 2021-06-01. 1) and the ResFinder database (downloaded on 20. 04. 2021)  [11]. Searches against the NCBI database were performed using AMRFinderPlus v3. 10. 5  [12]  , ABRicate v 1. 0. 1 ( https://github. com/tseemann/abricate ; Seemann, 2014) and DIAMOND (Galaxy Version 0. 9. 29. 0)  [13]. AMRFinderPlus was run in combined mode performing searches on both the genome sequence and predicted protein sequences. ABRicate searches were performed on the nucleotide version of the same database for both the genome sequence and predicted gene sequences.
The searches with DIAMOND were performed on the predicted protein sequences. The database searches were filtered at a minimum sequence identity of 80% and minimum coverage of 70%. Searches against the ResFinder database were performed using ABRicate v 1. 0. 1 and BLASTn (Galaxy Version 0. 3. 3). ABRicate searches were made on the genome sequence and predicted gene sequences. Search parameters included a minimum identity of 80% and minimum coverage of 70%. Since ResFinder is a nucleotide database, BLASTn searches were performed using the predicted gene sequences as a query. Searches were performed against the virulence factor database (VFDB)  [2 , 3]  full dataset (Accessed on 14. 07. 2021).
Data Availability SRX14185385: WGS of Lactiplantibacillus plantarum IMI 507027 (Original data) (NCBI) Lactiplantibacillus plantarum strain IMI 507027, whole genome shotgun sequencing project (Original data) (NCBI) Lactiplantibacillus plantarum IMI 507027 (Original data) (NCBI) Whole genome sequence data of Lactiplantibacillus plantarum IMI507027 (Original data) (Zenodo) CRediT Author Statement Ivana Nikodinoska: Data curation, Writing -original draft, Project administration; Jenny Makkonen: Methodology, Software, Writing -review & editing; Daniel Blande: Software, Formal analysis, Writing -review & editing; Colm Moran: Supervision, Project administration, Writing -review & editing.
Similarly, the psychological impact on the caregivers of patients with ADRD may be aggravated due to the pandemic. However, the relationship between social isolation and mental health in these patients and their caregivers during the pandemic has been insufficiently studied. Objective: We aimed to elucidate how social isolation and quarantine during the COVID-19 pandemic are associated with neuropsychiatric symptoms and mental health problems in patients with ADRD and their caregivers/families. Methods: In this preliminary review, we performed a literature search to identify studies on social isolation, symptom severity and concomitant negative experiences during the COVID-19 pandemic in patients with ADRD and their caregivers. We mainly searched the PubMed and Web of Science databases. Given that the COVID-19 pandemic is a relatively recent event, an electronic search was also performed using Google Scholar.
For visualization of the antibody-targeted epitope of HML-2, the predicted structure for endogenous retrovirus group K member 113 Env polyprotein was retrieved from the AlphaFold Protein Structure Database. 25 The molecular graphics and epitope visualization were performed using UCSF Chimera, a molecular modeling system developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco with support from NIH P41-GM103311. 26.
In a separate set of experiments, CSF (#9) was applied to neurons in the presence and absence of K01 or control IgG, and images were captured at 48, 60, 72, and 84 hours postexposure on the NanoEntek (Seoul, South Korea) JuLI Stage or BioTek (Winooski, VT) Cytation5/BioSpa bioimager. In another set of experiments, Env protein (100nM) was applied to the neurons in the presence or absence of K01 (3μg/ml), anti-CD98 (PIPA581032; Invitrogen, Carlsbad, CA; 3μg/ml), and control IgG (3 or 6μg/ml). High content imaging/analysis was achieved with GE Investigator 1. 93 analysis software and MetaMorph (Molecular Devices). Neuronal viability and neurite length were quantitated and plotted with GraphPad Software (San Diego, CA) Prism 7. 02.
1μl/min using a microinjector. Brain tissues were collected at 1 week postinjection, fixed in 4% paraformaldehyde (PFA) in 0. 1M phosphate-buffered saline (PBS), and cryopreserved in 10% sucrose in PBS and frozen until sectioning. The brain was cut into 30μm coronal sections containing the primary motor cortex. Sections ranging 1. 7mm from the bregma to 0. 1mm from the bregma at 200-to 300μm intervals were selected for staining with Cresyl violet solution (PS102-01; Fd Neurotechnologies, Columbia, MD). Lesion volume was estimated using Image J software. Apoptotic neurons were detected by In Situ Apoptosis detection kits (S7100; Millipore, Billerica, MA). Sections were counterstained with hematoxylin (Dako, Glostrup, Denmark). Images were processed using an Aperio whole slide scanner (Leica Biosystems, Nussloch, Germany).
HML-2 Env Causes Neurotoxicity We have shown that HML-2 Env expression can cause toxicity in human neurons in vitro and contribute to neurodegeneration in vivo. 21 To further investigate this, neurons were treated with increasing concentrations of recombinant HML-2 Env protein and assessed for neurotoxicity, in terms of neuronal cell counts and mean neurite length (Fig 1A  , B ). Neurons treated with 136nM Env protein displayed 35 to 40% loss of neurons and shortening of their neurites, and higher concentrations showed >80% neurotoxicity. To observe changes in electrophysiology and progressive morphological changes in neurons in response to HML-2 Env exposure, time course experiments were conducted (see Fig 1). Human neurons were seeded into a 48-well MEA plates for 28 days, and spontaneous electrical activity was recorded to establish baseline data prior to treatment.
(M) Spontaneous electrical activity was recorded at 24 hours after Env treatment. (N) Neurons were incubated with either K01 monoclonal antibody or nonimmune control antibody (3μg/ml) for 1 hour and then treated with 100nM Env protein, or Env was preincubated with K01 antibody for 1 hour at 37 C prior to addition of the complex to neurons at the same concentrations for 96 hours. Neurons were imaged, and neuronal cell counts were analyzed. These data represent mean + standard error of the mean from 3 separate determinants of 4 to 8 replicates, which were analyzed by analysis of variance and pairwise analysis with Tukey multiple comparison test. *p < 0. 5, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001. 3μg/ml. Subsequently, neurons were treated with 3μg/ml of either nonimmune IgG control antibody or the K01 antibody.
Discussion These data demonstrate a novel pathogenic mechanism of HERV-K subtype HML-2 on neurons mediated by its extracellular Env protein. This work has identified HML-2 Env receptors on the cell surface and the associated intracellular signaling pathways. Direct neurotoxicity in human neuronal cultures was investigated with the recombinant Env protein, and similar effects were recapitulated with ALS CSF, in which Env protein could be detected. HML-2 Env could be detected in the CSF of 12 of 15 ALS patients by digital Western blot, confirming its release and circulation in patients' body fluids with relevance to the central nervous system. We were unable to detect HML-2 Env in the CSF of healthy controls. However, previous studies have shown that expression of HML-2 is not specific for ALS and can be found in a number of cancers and other diseases.
Furthermore, the Env-mediated neurotoxicity was sensitive to heat inactivation of the protein, suggesting FIGURE 4: Amyotrophic lateral sclerosis (ALS) patient cerebrospinal fluid (CSF) impairs neuronal functioning. (A) CSF #3, #5, and #9 were diluted 100-fold in neuronal differentiation media and applied to human neuronal cultures. Spontaneous electrical activity (i and iii) and number of electrical bursts (ii and iv) were quantitated every 24 hours. Data are shown at 3 days (i and ii) and 7 days (iii and iv) postexposure. (B) Four images (2 Â 2) at Â10 magnification stitched together from the recording wells show neurons on the electrodes that correspond to Panel A above at 3 (top) and 7 (bottom) days. (C) Neurons were treated with media, K01 (3μg/ml), and control Ig (3μg/ml) prior to exposure to ALS CSF #3 or #9 (100-fold dilution) in triplicate.
At 4 days after CSF treatment, spontaneous electrical activity and mean firing rate were analyzed. Data in A and C represent the mean and standard error of the mean of 10 replicates per condition and were analyzed by analysis of variance and pairwise analysis with Tukey multiple comparison test. *p < 0. 05, **p < 0. 01, ***p < 0. 001. that the toxicity was likely due to a conformationally dependent epitope of Env. The neurotoxicity of the Env protein is not unique to HML-2. We mapped the binding site of a neutralizing antibody to identify the region of the protein responsible for the neurotoxicity, which is located at amino acids Ser298-Pro312. An extensive body of literature exists on the neurotoxic properties of the Env protein of the human immunodeficiency virus (HIV) and its Tat protein, which is spliced from the env gene (reviewed in  Nath 29  ).
Neurons were imaged, and neuronal cell counts were analyzed. These data represent mean + standard error of the mean from 3 separate determinants of 4 to 8 replicates, which were analyzed by analysis of variance and pairwise analysis with Tukey multiple comparison test. *p < 0. 5, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001.
The average volume percent of Si precipitates and the size of the particles are calculated to be 22% and 1. 32 µm, respectively, using ImageJ software. The average volume percent of Fe-rich precipitates in SHT and aged specimens was calculated to be 5. 9% and 6. 12%, respectively, which may contribute to the enhanced mechanical properties of the alloy. It can be inferred from the hardness curve that the maximum hardness is obtained at 12 h and 8 h for 140 °C and 160 °C, respectively. However, it is efficient to perform heat treatment at 160 °C as it will promote the achievement of desirable hardness results at a shorter duration compared to performing heat treatment at 140 °C. Hardness goes down after these optimized hours due to over-aging as the size of the precipitates grows bigger and the dislocations-precipitation interaction changes.
Eutectic Silicon spheroidizes at elevated temperatures due to the increase in size and surface perturbations occurring at the interface, resulting in the formation of near-spherical Si particles. The average volume percent of Si precipitates and the size of the particles are calculated to be 22% and 1. 32 µm, respectively, using ImageJ software. The average volume percent of Fe-rich precipitates in SHT and aged specimens was calculated to be 5. 9% and 6. 12%, respectively, which may contribute to the enhanced mechanical properties of the alloy. Room temperature tensile testing was performed on the as-built and heat-treated specimens and the corresponding engineering stress-strain curves and tensile properties are provided in Figure  8  and Table  2 , respectively. The mechanical properties of AMed AlSi10Mg are often compared to the as-cast A360 alloy due to the similar composition and they both constitute an Al-Si system with microstructures containing α-Al grains in a eutectic Al-Si matrix  [24].
However, the improvement of ductility can be explained by the dependency of tensile ductility on grain orientation in the heat-treated samples  [26]. This is also in agreement with studies by Han and Jiao  [22]  that showed a substantial increase in elongation to fracture from 6 to 22% due to grain growth associated with Si precipitation, and the thermal residual stress release that occurred during heat treatment. Surprisingly, the yield strength of the AA (160 • C) samples shows an 11. 4% increase compared to that of AA (140 • C). This contradicts the hardness data that showed a slight increase at the peak for AA (140 • C) samples. A similar trend was observed in additively manufactured AlSi10Mg by Girelli et al. [27]  where lower hardness values were recorded at higher aging temperatures and were correlated to the presence of porosity defects.
This work provides an overall assessment of microstructural characterization and mechanical properties of AlSi10Mg produced by selective laser melting process and identified the impact of T6-like conventional heat treatment. The results obtained could be used as a manufacturability reference to produce SLM'ed AlSi10Mg at optimized parameters, and to obtain better control of the microstructural and mechanical properties. Acknowledgments: Authors wish to acknowledge the  Natural Sciences and Engineering Research Council (NSERC) Canada  for the financial support and  Peter Walker  from  Carleton University  for support in metallography and SEM analysis.
Data sources The Uganda Demographic and Health Survey (UDHS) was a cross-sectional, nationally representative data conducted in 2016 by the Uganda Bureau of Statistics (UBOS) between June and December 2016  [9]. The UDHS project aimed to provide recent evidence on basic demographic and health indicators (key demographic indicators such as fertility, under-ve, and adult mortality; contraceptive knowledge and practice; malaria prevalence; child feeding practices; a key aspect of child and maternal health; key education indicators; extend of gender-based violence and disability. [3]  We used data based on the survey questionnaire (household), where demographic information and person characteristics were collected (age, sex, marital status, education, relationship with the household head). The UDHS also collected information on the money paid by households for health care services.
Methods Descriptive statistics were used to provide more insight into the study sample. Then, we estimated the simple and multivariate "probit" models to investigate characteristics and factors associated with health nancial risk. We estimated the following multivariate econometric equation: Where, Financialrisk i represents the dependent variable to explain. Disability i is a binary variable and de ne as "Yes" if the household's head reported any form of functional limitation and "No" elsewhere. X i represents other explanatory variables. β i stands or the parameter to estimate. is the error term. We used the STATA SE 64 statistical software 14. 2 (StataCorp, LP, College Station, TX, USA) for statistical and econometric analysis. Footnote: [3] https://dhsprogram. com/pubs/pdf/FR333/FR333.
pdf  [4]  https://dhsprogram. com/data/dataset/Uganda_Standard-DHS_2016. cfm? ag=0  [5]  It is important to note the number of family having access to health insurance through employer; social security; and other privately purchased commercial health insurance were quite low in Uganda. [6]https://www. who. int/standards/classi cations/international-classi cation-of-functioning-disabilityand-health/who-disability-assessment-schedule  [7]  This approach provides basic essential information on disability comparable to those collected worldwide via Washington Group (WG) disability tools. Based on the household questionnaire, respondents were aged 15 or above. [8] https://dhsprogram. com/data/dataset/Uganda_Standard-DHS_2016. cfm? ag=0 3. Results.
Following quantification by Qubit (Thermo Scientific), obtained libraries were analyzed on a V3-150 chip (Illumina) by MiSeq sequencing device (Illumina). The resulting reads were analyzed using a script written in Python 3 language as described elsewhere. [35] NA Preparation and Purification: DNA templates were PCR-amplified using Ampli-Forward and Ampli-Reverse primers. PCR products were transcribed after mixing them with 25 mm MgCl 2 , 40 mm Tris-HCl pH 8. 1 (at 37 °C), 5 mm DTT, 1 mm spermidine, 1. 6 mm each of rNTP and T7 RNA polymerase and an incubation for 2 h at 37 °C. The obtained RNA was extracted using phenol/chloroform and purified by preparative gel electrophoresis as described previously. [34] NA Analysis: RNA characterization was performed using 400 nm RNA in refolding buffer (10 mm MgCl 2 or as specified, 40 mm Tris-HCl pH 8.
Acknowledgements The authors thank  Emilie Geersens  for fruitful discussions,  Marie Vandroux  for technical assistance, as well as  Sandrine Koechler  and  Abdelmalek Alioua  ( IBMP Gene Expression Analysis facility ) for technical assistance with high-throughput sequencing. The authors are grateful to  Magali Frugier  for her critical reading of the manuscript. This work received financial support from the  Agence Nationale de la Recherche  ( DehalofluidX  project  ANR-17-CE07-0009  and  MICROFLUOR  project  ANR-21-CE04-0010 ). This work was performed within the  Interdisciplinary Thematic Institute "IMCBio" (ITI 2021-2028 program  of  University of Strasbourg, CNRS and Inserm ), and also supported by  IdEx Unistra  ( ANR-10-IDEX-0002 ),  SFRI-STRAT ' US  project ( ANR-20-SFRI0012 ), and  EUR IMCBio  ( ANR-17-EURE-0023 ) under the framework of the  French Investments for the Future Program  and of the previous  LabEx NetRNA  ( ANR-10-LABX-0036 ), and also supported by the  Centre National de la Recherche Scientifique (CNRS) ,  Université de Strasbourg, and its Initiative of Excellence (IdEx).
We additionally demonstrate how labels used in the popular Freesurfer (FS7)  [22]  and Automatic Segmentation of Hippocampal Subfields (ASHS)  [13]  software packages can be applied under our topologically-constrained framework. Altogether, we combine novel U-Net tissue classification, previously developed hippocampal unfolding  [12] , and topologically-constrained subfield labelling  [21]  together into a single pipeline which we refer to as 'HippUnfold' hereinafter. We designed this pipeline to employ FAIR principles (findability, accessibility, interoperability, reusability) with support across a wide range of use-cases centered around sub-millimetric MRI.
4T ex vivo hippocampal subfield segmentations  [22]. When hippocampi take on different folding configurations, such registrations can become illposed. HippUnfold overcomes these limitations in two ways: with extensive training (in this case n=590), U-Net can capture detailed inter-individual differences in folding and, secondly, our unfolding technique ensures that subfield labelling is topologically constrained  [19]. We made use of 100 randomly-chosen subjects from the HCP-Aging dataset to compare the approach with the FS7 hippocampal subfields pipeline and ASHS using a recent manual subfield multi-atlas  [29]. Figure  3A  shows a side-by-side comparison of HippUnfold, ASHS, and FS7 to one representative 81 y. o. female. Figure  3B  shows Bland-Altmann plots comparing subfields CA1, CA3, and subiculum volume across the three methods in all 100 subjects, as well as their correlation with subjects' ages.
Similar errors have been documented for FS in other recent work  [30, 31]. Trained U-Net performance is similar to manual segmentation From the HCP-YA dataset, a set of 738 (left and right from 369 subjects) gold standard hippocampal tissue (that is, hippocampal GM and surrounding structures) segmentations were generated according to the manual protocol defined in  [21]. Specifically, this was done by raters JD, MY, and BK using an incremental learning U-Net training regime described in the Materials and Methods nnUNet training section. Automated tissue segmentation was performed using nnUNet, a recent and highly generalizable implementation of a U-Net architecture  [11]. This software was trained on 80% (n=590) of the gold standard segmentation data described above, with the remaining 20% (n=148) making up a test set.
Left and right hippocampi from the same participant were never split across training and testing sets due to their high symmetry. Note that all input images were preprocessed, resampled, and cropped (see Figure  1  and Materials and Methods) prior to training. Within the training set, 5-fold cross-validation was performed as implemented in the nnUNet code. Training took place on an NVIDIA T4 Turing GPU over 72 hours. This process was carried out using either T1w or T2w input data with the same training/testing data split. All default nnUNet data augmentation and hyperparameters were used. Figure  5. Test set performance in Dice overlaps between HippUnfold and manually unfolded subfields. All values are compared to ground truth manually defined tissues followed by unfolded subfield definition (manual unfold) to determine how small differences in gray matter parcellation propagate through the unfolding, subfield definition, and re-folding.
Two models were trained in parallel using the same labels but different input MRI data modalities consisting of T1w or T2w data. Dotted black lines indicate corresponding values from  [13] , who include SRLM in all labels and combine CA4 and DG into one label. Dice overlap depends heavily on the size of the label in question, being lower for smaller labels. Typically a score of >0. 7 is considered good, and many fully manual protocols show dice scores of >0. 8 for the larger subfields like CA1 or the subiculum, and 0. 6-0. 8 for smaller subfields like CA2 or CA3 (see  [18]  for overview). Within the HCP-YA test set, performance was similar or better than most fully manual protocols for T1w and T2w data. Performance on T1w images was only marginally poorer than T2w images which typically better show the SRLM and are popular in manual subfield segmentation protocols  [18].
Generalizability to unseen datasets and populations We aimed to determine whether our pipeline would generalize to unseen datasets with different acquisition protocols and sample populations. Hippocampal morphometry, integrity, and subfields are often of interest in disease states where atrophy or other structural abnormalities are observed  [1, [32] [33] [34]. For this reason, we examined the HCP-A datasets in which we anticipated cases of severe atrophy would be present in some older subjects. Figure  6A  shows results from one representative individual (an 80 y. o. female with signs of age-related atrophy but good scan quality). Another common use-case for hippocampal subfield segmentation is on anisotropic T2w data which is considered optimal for performing manual segmentation in most protocols  [18] , but may impose challenges for our method due to the difference in resolution.