dataesr/scientific-paragraphs-categorization huggingface dataset:
The localization of ORP5-ORP8 PLA signals to ER-PM contact sites was analyzed in HeLa cells transfected with RFP-PH-PLCd, to stain the PM, and Mito-BFP, to label mitochondria. However, only a minor pool of ORP5-8 PLA spots was found in contact with the PM (4% of endogenous ORP5-ORP8 and 5% of co-overexpressed ORP5-ORP8) (Figures  2D-2F ). The localization of ORP5-ORP8 PLA spots to the ER, including MAMs, was confirmed in cells co-expressing the ER protein Sec22b and the mitochondrial-targeted Mito-BFP (Figure  S3C ). Overall, these data reveal that the main sites where ORP5 and ORP8 localize and interact in endogenous physiological conditions are the ER-mitochondria contact sites, and not the ER-PM contact sites. ORP5 and ORP8 physically interact with the MIB complex facing CJs To investigate whether ORP5/8 localize to specific ER-mitochondria contact subdomains, we performed a morphological analysis of ORP5 localization by immuno-electron microscopy (IEM) on ultrathin cryosections from HeLa cells transfected with HA-ORP5 or EGFP-ORP5 (as endogenous ORP5/8 levels are too low to be detected by IEM).
Interestingly, a significant decrease (of about 40%) in ORP5-ORP8 interaction in close proximity to mitochondria (corresponding to MAM) was found in both SAM50 and Mic60 KD cells, compared with control cells  (Figures 5A and 5B) , indicating a synergistic effect of SAM50/Mic60 on the ORP5-ORP8 interaction at MAM. Further localization analysis of endogenous ORP5 and ORP8 in siSAM50 cells confirmed decreased levels of these proteins at MAM (Figures  5C-5F ). Together, our data reveal the specificity of the effects of SAM50 KD on ORP5 and ORP8 interaction with each other and with components of the MIB complex. To verify the possibility of an indirect effect of SAM50 or Mic60 silencing on the morphology and abundance of MAMs, we carried out an ultrastructural analysis by conventional electron microscopy (EM) and horseradish peroxidase (HRP)-KDEL EM (carrying an HRP tagged with the ER retention motif of the [Lys-Asp-Glu-Leu] endoplasmic reticulum protein retention receptor 1 to stain the ER) in Mic60 or SAM50 silenced cells.
Treatment with 5 mM hydroxylamine robustly inhibited PS-to-PE conversion in both control and ORP5 KD cells, the level of residual conversion being similar in both of these cells, further confirming that the reduction in mitochondrial PE induced by depletion of ORP5 is essentially due to the decrease in PS transfer from the ER to the mitochondria (Figure  S8E ). The b-chloro-L-alanine and hydroxylamine data also suggest that at least 80% of the serine labeling of PE occurs via the PS decarboxylase reaction in HeLa cells, in accord with a previous work in another cell type, the baby hamster kidney fibroblasts (BHK cells), showing that only certain minor PE species are labeled from the sphingosine-PE pathway  (Heikinheimo and Somerharju, 1998). To test whether the effects on PS transport at ER-mitochondria contacts were specific for ORP5 and ORP8 loss of function or simply due to a decrease of ER-mitochondria contacts induced by their KD, we quantified the abundance of ER-mitochondria contact sites by EM in control and ORP5, ORP8, or ORP5 + ORP8 KD cells.
To test whether the interaction of ORP5 with the MIB complex could facilitate the non-vesicular transfer of PS from the ER to the mitochondrial membranes (and consequently synthesis of mitochondrial PE), we performed radiometric PS-to-PE conversion (C) HeLa cells transfected with siCtrl, siORP5, siORP8, or siORP5+ORP8 RNAi oligos were incubated with L-[ 3 H(G)]serine (30. 9 Ci/mmol) for 18 h. After extraction and separation of lipids by TLC, PS and PE spots were scraped and analyzed for [ 3 H] radioactivity, as described in STAR Methods. Each condition was analyzed in triplicate in each of three independent biological replicates. Data are presented as mean of PE:PS ratio ± SEM. Statistical analysis: unpaired Student's t test, *p < 0. 05, **p < 0. 01 compared with Ctrl. (D) Cells transfected with siCtrl and siORP5 oligos were treated with 1 mM b-chloro-L-alanine (CA, b-Chl-L-ala, inhibitor of Ser-palmitoyltransferase) or untreated, then pulsed with 7 mCi/mL of [3H(G)]serine for 1 h and chased for 4 h in serum-free DMEM + b-chloro-L-alanine, before analysis.
STAR+METHODS Detailed methods are provided in the online version of this paper and include the following:   1:1000; SAM50 (SIGMA, HPA034537) 1:1000; Mic60 (Proteintech, 10179-1-AP) 1:1000; metaxin 2 (Santa Cruz, sc-514231) 1:1000; TOM20 (BD Transduction Laboratories, 612278) 1:10000; PDI (GeneTex, GTX30716) 1:500; VAPB (SIGMA, HPA013144) 1:500; PSS1 (PTDSS1, SIGMA, HPA016852) 1:300; PISD (SIGMA, HPA031090) 1:300; GFP (Roche, 11814460001) 1:1000; anti-mouse-HRP (GE Healthcare, NA931V) 1:10000; anti-rabbit-HRP (GE Healthcare, NA934V) 1:10000.
STAR+METHODS KEY RESOURCES Mass spectrometry-proteomic analysis Mass Spectrometry (MS) analysis was carried out by the proteomics/mass spectrometry platform of IJM (http://www. ijm. fr/ plateformes/spectrometrie-de-masse). Briefly, after washes with binding buffer, immunoprecipitations beads were rinsed with 100 mL of NH4HCO3 25 mmol/L. Proteins on beads were digested overnight at 37 C by sequencing grade trypsin (12. 5 mg/mL; Promega Madison, Wi, USA) in 20 mL of NH4HCO3 25 mmol/L. Digests were analysed by an Orbitrap Fusion (Thermo Fisher Scientific, San Jose, CA) equipped with a Thermo Scientific EASY-Spray nanoelectrospray ion source and coupled to an Easy nano-LC Proxeon 1000 system (Thermo Fisher Scientific, San Jose, CA). MS/MS data were processed with Proteome Discoverer 1. 4 software (Thermo Fisher scientific, San Jose, CA) coupled to an in-house Mascot search server (Matrix Science, Boston, MA; version 2.
4. 2). MS/MS data were searched against SwissProt databases with Homo sapiens taxonomy. The Mascot score for a protein is the summed score for the individual peptides, e. g. peptide masses and peptide fragment ion masses, for all peptides matching a given protein. For a positive protein identification, the mascot score has to be above the 95% confidence level. In Mascot, the ions score for an MS/ MS match is based on the calculated probability, P, that the observed match between the experimental data and the database sequence is a random event. The reported score is À10Log 10 (P). A score of 200 indicates a probability of 10 À20. Scores greater than 70 are significant, while scores lower than 40 should not be considered or carefully validated at MS/MS level (source: http:// www. matrixscience.
A. 1. 4, Leica) using the LAS-X software. Fluorescence was excited using either a 405 nm laser diode or a white light laser, and later collected after adjusting the spectral windows with GaAsP PMTs or Hybrid detectors. Images from a mid-focal plane are shown. Images were processed and fluorescence was analysed off line using Image J. For co-localization analysis of fluorescent signals, the acquired images were processed using the In situ proximity ligation assay (PLA) The protein-protein interactions in fixed HeLa cells were assessed using in situ PLA (DuolinkâSIGMA) according with the manufacturer's instructions. Briefly, HeLa cells seeded on 13 mm glass coverslips (Agar Scientific) were incubated with MitoTracker Red (mitochondrial marker, Invitrogen, 1 mM in DMEM) for 30 min at 37 C or co-transfected with PHPLCd-RFP (plasma membrane marker) plus Mito-BFP (mitochondrial marker).
Polymerase solution was washed out from the coverslips with 13 wash buffer B and 0. 013 wash buffer B. Vectashield Mounting Medium with or without DAPI (Vector Laboratories) was used for mounting. Images were acquired on Confocal inverted microscope SP8-X (DMI 6000 Leica). Optical sections were acquired with a Plan Apo 633 oil immersion objective (N. A. 1. 4, Leica) using the LAS-X software. Fluorescence was excited using either a 405nm laser diode or a white light laser, and later collected after adjusting the spectral windows with GaAsP PMTs or Hybrid detectors. Images from a mid-focal plane or maximal projection of all layers are shown. Images were processed and the number and the distance of PLA dots to mitochondria and to the plasma membrane were assessed using the Imaris software (v 9.
3, Bitplane). Briefly, segmented 3D images (PLA foci identified as ''spots'', mitochondria identified as ''surfaces'', and plasma membrane represented as ''cell'' were generated from confocal Z-stack images and the shortest distance between each spot center and the nearest point of the surface or cell object was calculated based on a 3D distance map. Spots objects (PLA dots) with a distance smaller than 380nm from surfaces (mitochondria) and cell (plasma membrane) objects were considered at a close proximity of these objects. The threshold of 380 nm was used as an estimation of the PLA reaction precision including both primary and secondary antibodies (30nm) plus half the FWHM of the PLA amplification signals (350nm). Antibodies and dilution used for PLA were as follows: ORP5 (SIGMA, HPA038712) 1:150; ORP8 (Santa Cruz,sc-134408) 1:150; ORP8 (GeneTex, GTX121273) 1:150; SAM50 (SIGMA, HPA034537) 1:200; metaxin 2 (Santa Cruz, sc-514231) 1:150; TOM20 (BD Transduction Laboratories, 612278) 1:150.
All data are presented as mean ± SEM of three experimental replicates. For the quantification of ER-mitochondria contact sites in HRP-stained Epon sections, the total circumference of each mitochondria and the length of the multiple HRP-positive ER segments closely associated (<30 nm) with them were measured by manual drawing using the iTEM software (Olympus), as in  (Galmes et al. , 2016; Giordano et al. , 2013) , on acquired micrographs of HeLa cells for each cell profile, as indicated in the figure legends. Cells were randomly selected for analysis without prior knowledge of transfected plasmid or siRNA. All data are presented as mean (%) ±SEM of three experimental replicates. For the quantifications of the total mitochondria surface the total circumference of each mitochondria was measured by manual drawing using the iTEM software (Olympus), and data are shown as average of total mitochondrial surface length (mm)/cell ±SD of three experimental replicates.
For the quantification of ORP5 immunogold labeling on ultrathin cryosections, 150 gold particles localized at ER-mitochondria contact sites were counted on acquired micrographs of randomly selected cell profiles at specific ranges of distance from CJ (0-50, 50-100, 100-150, 150-200 nm) in each of three experiments. All data are presented as mean (%) ±SEM of three technical replicates.
ACKNOWLEDGMENTS We thank  Dr V. Kozjak-Pavlovic  and  P. Somerharju  for kindly sharing reagents and advice with us. We also thank  Dr. R. Legouis  and  Dr. Emmanuel Culetto  for discussion and for critically reading the manuscript;  Claire Boulogne ,  Sandrine Le  ´cart, and  Remi Le Borgne  for help and consultation with microscopy experiments; and  Valentin Guyard ,  Blandine Bourigault ,  Riikka Kosonen , and  Liisa Arala  for technical assistance. The present work has benefited from the  Imagerie-Gif core facility  supported by  I'Aslgence Nationale de la Recherche  ( ANR-11-EQPX-0029 /Morphoscope ,  ANR-10-INBS-04 / FranceBioImaging ;  ANR-11-IDEX-0003-02/Saclay Plant Sciences ). For the Immuno-EM and HRP-KDEL EM analysis/quantifications we acknowledge the  ImagoSeine facility , a member of the  France BioImaging infrastructure supported by  grant  ANR-10-INBS-04  from the  French National Research Agency.
4] [25]  However, they were seldom applied to climate projections to predict the future evolution of vector risk. To date, a single study used mechanistic models to predict the future evolution of densities of one Aedes species, Ae. aegypti, at a global scale,  25  but with no validation of temporal dynamics. Because such models rely on strong hypotheses about mechanistic processes, confidence in future predictions can only arise from the comparison and confrontation of results from independently built models or independent data. In this study, a compartment process-based model was used to describe seasonal variations of densities of two Aedes mosquito species, Ae. aegypti and Ae. albopictus, in response to contemporary and future climates. 7] [28] [29] [30]  To validate the model seasonal dynamics, we used original density data from temporal entomological surveys from two Southeast Asian cities: Phnom Penh, Cambodia, and Vientiane, Lao People's Democratic Republic (here after Lao PDR).
Based on climate projections from a range of climate models and scenarios of greenhouse gas emissions (Worldclim database  31  ; https://www. worldclim. org/ data/index. html), predictions about the evolution of densities of both species were mapped over selected future periods of the 21st century. Our results were used to both discuss the potential vector evolutions with the diversity of future potential climates but also the advantages and flaws of mechanistic approaches in comparison with other statistical modeling. Overall, the framework allows us to discuss the magnitudes of predictions uncertainties, which are key to identify future improvements.
Climate Data Population dynamics were modeled using seasonal variations of climate variables (surface air temperatures and precipitation) from contemporary data and from climate models using future projections. These data were obtained from the WorldClim initiative  31  (https://www. worldclim. org/) at a monthly scale. As the model uses daily inputs, climate data were interpolated linearly to obtain daily values. The contemporary seasonal climate corresponded to the 1970-2000 period. Future projections were based on nine climate models (BCC-CSM2-MR,  38  CNRM-CM6-1, 39 CNRM-ESM2-1,  40  CanESM5,  41  GFDL-ESM4,  42  IPSL-CM6A-LR,  43  MIROC-ES2L,  44  MIROC6,  45  and MRI-ESM2-0  46  ) for four scenarios of greenhouse gas emissions (Shared Socioeconomic Pathways: SSP1 2. 6, SSP2 4. 5, SSP3 7.
Because occurrence data was available on a 0. 01-degree grid, land cover data were converted to this scale by computing proportions of each land cover category in each grid cell. Topography data was available at a 90 m spatial resolution but converted to 0. 01°by computing elevation and slope averages and variability of slope in each grid cell. An ensemble modeling approach was used to model presence/ absence as dependent on land cover and topography. Ensemble modeling was performed using the biomod2 R package (version 4. 0. 3; R Development Core Team), considering a combination of generalized linear modeling (GLM), gradient boosting modeling (GBM), classification tree analysis (CTA), artificial neural network (ANN), flexible discriminant analysis (FDA) and random forest (RF) to compute spatial predictions of probability of observation.
Validation of Contemporary Temporal Dynamics Entomological survey data from Phnom Penh and Vientiane were used to estimate the seasonal dynamics of Ae. albopictus and Ae. aegypti densities. In Phnom Penh, surveys consisted in the sampling of 40 pagodas in the city (Figure  S4 ), using 5 ovitraps per pagoda picked up every 8 wk between March 2019 and February 2020, resulting in 1,033 sampling points. Ovitraps without filter paper (black buckets)  49  were used to collect immature stages (larvae), which were then emerged in laboratory for species identification using morphological characters. 50 T -T E TDD E if T > T E 0 otherwise 8 > < > : 24q T K 298 e DH A R 1 298 -1 T K ð Þ 1 + e DH H R 1 T 1=2H -1 T K À Á With q = 0:01066; DH A = 10,798:18; DH H = 100,000; T 1=2H = 14,184:5 f L Transition function from larva to pupa q 1 T 2 + q 2 T + q 3 with q 1 = -0:0007; q 2 = 0:0392; q 3 = -0:3911 24q T K 298 e DH A R 1 298 -1 T K ð Þ 1 + e DH H R 1 T 1=2H -1 T K À Á With q = 0:00873; DH A = q 1 T 2 + q 2 T + q 3 with q 1 = -0:0008; q 2 = 0:0051; q 3 = -0:319  Note: Adapted from Table  3  in Tran et al.
Seasonal variations of densities were assessed using climate data at a monthly scale. This process did not allow us to account for the effects of extreme climate events occurring at a submonthly scale and responsible for extreme values of temperature or precipitation. For instance, extreme rainfall events can result in a drop in egg, larva, and pupa densities due to the washing of breeding sites, yet such mechanism could not be accounted for here due to the smoothing of monthly climate data. As pointed out in the IPCC reports,  51, 52  such extreme events are forecast to increase in the future and will need to be considered in future studies. Considering the objective of asserting the impact of climate over Aedes densities, only rain-filled breeding sites were considered in the modeling framework.
The presence of human-filled breeding sites (e. g. , water storage containers, flower vases) typically found in urban settings where the SDM model predicts highest probabilities of occurrence (Figure  S3B ) could attenuate the effect of rainfall over density variations. ] [71]  Although seasonal variability of mosquito density was assessed through the process-based model, its baseline spatial variability was estimated with statistical SDMs. SDMs predicted higher probability of presence in urban areas (high proportion of impervious surface land cover type) for both species. This pattern could be due to some extent to an observational bias in the occurrence database, with populated areas potentially more likely to be surveyed than rural areas. However, the potential observational bias is only pertinent when examining contemporary density maps but has no consequences for the conclusions about the future relative evolution of densities, which did not depend on SDM outputs.
79 Markrelease-recapture methods are able to approximate consistently the abundance of mosquitoes in different locations  [80] [81] [82] [83]  but are very costly and time-consuming. Field data from Phnom Penh and Vientiane were used here to estimate only seasonal variations of Aedes densities. In Phnom Penh, records covered only a single year of sampling and were therefore not likely to be fully representative of the seasonal variations of densities in the location. Still, seasonal dynamics of densities, although contrasted between the two species, appeared to both match with outputs from the process-based model.
Further Uses of Modeled Mosquito Densities for Vectorborne Diseases Model outputs describing vector risk can be used in different ways to investigate how it translates into disease risk. Such processbased model outputs have indeed been used as input in dengue mechanistic transmission models. 84 Temporally variable indices of adult density, for instance those modeled from historical observed gridded climate data (e. g. , from the Worldclim data set), could also be used in statistical models as an independent covariate to build better disease predictive models when long-term data from density surveys are not available. Outputs from large-scale process-based models of Ae. aegypti density have indeed been shown to correlate with local dengue fever caseload. 85 Yet, causal relationships between vector density and disease risk are not completely apprehended for diseases like dengue fever  11, 86  as a result of a lack of long-term reliable longitudinal entomological survey data.
5°t o 50°with a step size of 0. 007°, a time per step of 65 s, and a total of 32 min per scan. The patterns were recorded a few minutes after sample preparation and the addition of solvent. For some samples repeated patterns were recorded to make sure that swelling is saturated and does not increase over time. Experiments with heating and cooling were performed at the Rossendorf Beamline (BM20) of the European synchrotron radiation facility (ESRF),  46  using a CyroStream 800 system (Oxford Cryosystems) and radiation wavelength λ = 0. 7381 Å. The MXene powder was loaded into 0. 7-1 mm capillaries with excess liquid solvent and sealed to prevent solvent evaporation. Experimental data were collected in transmission geometry using a Pilatus3 X 2M detector and extracted with Bubble software. 47 The detector geometry parameters were calibrated with PyFAI using the NIST standard LaB 6.
Acknowledgements A. T. acknowledges funding from the  European Union 's  Horizon 2020 research and the innovation program  under grant agreement no. 881603. A. T. acknowledges support from the  Swedish Research Council  (grant no. 2017-04173 ) and  Energimyndigheten  (no. 50620-1 ). A. T. also acknowledge the  Vibrational Spectroscopy Platform of Umeå University  and  A. Shchukarev  for support with the XPS characterization.
Proton Nuclear Magnetic Resonance Spectroscopy Analysis The EPSs proton nuclear magnetic resonance spectroscopy ( 1 H-NMR) was recorded in 25 µL deuterated water (D 2 O) on Bruker ASX400-WB spectrometer equipped with a double resonance ( 1 H/X) Broad Band Inverse z-gradient probe head. Chemical shifts were expressed in ppm downfield from the signal of the methyl group of internal acetones ( 1 H 2. 225 ppm at 27 • C). The samples were analyzed in 5 mm susceptibility matched tubes (Shigemi, Japan). Integration of spectra and data analyses were performed with MESTRENOVA (version 2016).
Thermal Gravimetric Analysis The thermal gravimetric analysis (TGA) of G. gelatinosa EPSs was evaluated on a Pyris 1 TGA (PerkinElmer, Texas, USA) according to the standard DIN ISO 11358. EPSs sample (20 mg) was heated, in the range of 20-900 • C, under a nitrogen atmosphere with a flow rate of 10 mL min -1 and a heating rate of 10 • C min -1. Data are presented as weight loss (%) as a function of temperature.
Data collection 2. 3. 1. Inclusion For each participant, a questionnaire was completed at inclusion. The questionnaire addressed demographic characteristics (age, sex, place of residence, marital status, number of children, history of anxiety, depression, or burn-out disorders, consumption of tobacco, alcohol, coffee, and anxiolytics) use of psychological support, personal organizational characteristics (mode and length of commute, family organization during confinement, temporary accommodation) and professional characteristics (profession, type of hospital, years of professional experience, usual work position and reassignments, managerial responsibility). They also completed specific questionnaires regarding anxiety, depression, and stress. The questionnaire surveys were anonymous and personal information was not disclosed, except for demographic data.
Statistical analysis Continuous data were described by means (±standard deviation), and categorical ones by frequencies and percentages. The changes in anxiety, depression, and stress levels over time were modelled by a linear mixed model including a period effect and a continuous time effect within periods (and possibly an interaction). Then, the occupation (and possibly an interaction with the period) and the number of work days, night shifts, and 24-hour work shifts were progressively introduced in the model depending on their significance. A random intercept by healthcare worker was added in the model. Once the base model was defined, several other factors were assessed, one at a time: age class, sex, marital status, children, changes in family organization, usual work position, years of professional experience, previous psychiatric history, COVID-19 infection, work disability related to infection or that of a loved one, managerial responsibility.
The effect of the factors on anxiety/depression/stress was quantified by slope or difference of means with the associated 95 % Confidence Interval [95 % CI]. No correction for multiple testing was performed. A McNemar test was used to compare between the beginning and the end of the study the consumption of alcohol, anxiolytics, tobacco, and coffee, as well as the use of psychological support. P-values <0. 05 were considered significant. The analyses were performed using the SAS 9. 3 and R (4. 0. 2) software (main procedure/package: proc. glimmix/package lme4)  [20].