dataesr/scientific-paragraphs-categorization huggingface dataset:
For the transportation time, it was assumed that based on the size of the tested countries, products were distributed from the factory to retailers for a period up to 12 h, the transportation time was thus described by a uniform distribution as follows: t tr Uniform(2; 12) (13) Given that UHT products considered as shelf-stable, they can be transferred either by insulated or non-insulated trucks. Temperature in insulated trucks was assumed to remain below 25 • C (our best knowledge) and did not allow growth. The percentage of insulated truck was described through a Bernoulli distribution with Uniform distribution capturing the uncertainty as follows: Bernoulli(1, P truck ) (14) P truck Uniform(0. 1; 0. 5) (15) Temperature inside non-insulated trucks was monitored through data loggers for a period of one month (August) during transportation in Greece, an empirical distribution was built using the recorded data.
Due to lack of temperature data inside trucks in Poland, historical hourly outdoor temperature data for the same period were retrieved from an online database (www. wunderground. com) and used to build an empirical distribution. The duration of the domestic storage was set to 120 days to take into account the worst-case scenario during summer period, while the temperature of domestic storage for both seasons was described by two probabilistic distributions build as follows. Historical hourly temperature data for Poland (Warsaw) and Greece (Athens) between June and September and November to February 2021 were retrieved from an online database (www. wunderground. com). To assess the variability, hourly temperature data for each country were divided into two parts, representing temperature fluctuation during day and night.
More specifically, data retrieved from 9 am to 9 pm were included in the temperature distribution of day, while data obtained from 9 pm to 9 am were included in the temperature distribution of night. Both day and night temperature data were used to build empirical distributions. Overall, four empirical distributions were built per country. The maximum specific growth rate (μ max ) was estimated individually for transportation, day and night storage as a function of temperature and pH, and a gamma model was applied as follows: μ max = μ opt *γ(T)*γ(pH) (16) The term γ(Τ) represents the Cardinal model with Inflection proposed by  Rosso et al. (1993)  for temperature and it written according to the following equation: γ(T)= (T -T min ) 2 (T -T max ) ( T opt -T min )[( T opt -T min )( T -T opt ) - ( T opt -T max )( T opt +T min -2T )]+ε 2 (17) ε 2 Normal(0, sd 2 ) (18) Where: T min , T opt and T max are the theoretical minimum, optimum and maximum values of temperature enabling growth ( • C).
Model implementation The spoilage risk assessment model was implemented in R software (R Core Team, 2022). Fitting of distributions was performed by using the fitdistrplus package  (Delignette-Muller & Dutang, 2015). The second order Monte Carlo simulation, that was used to propagate uncertainty and variability separately, was carried out using the mc2d package  (Pouillot & Delignette-Muller, 2010). The number of iterations performed for uncertainty was 1,000 and for variability 10,000. Results are reported with their confidence interval capturing the uncertainty dimension.
3) without an A/C system (Fig. 2a2 ). The estimated risk of spoilage due to the growth of G. stearothermophilus in plant-based milk alternatives transported and stored in North (Poland) and South Europe (Greece) under the current climatic conditions is presented in Table  2. As expected, there is no risk of spoilage during the wintertime for both countries since the recorded historical temperature for 2022 did not exceed the minimum growth temperature of G. stearothermophilus. On the contrary, based on the recorded temperature data growth was observed in both countries during summertime. Interestingly, the final concentration of G. stearothermophilus found in a plant-milk alternative distributed and stored in Poland did not exceed the N max , and therefore no risk of spoilage was estimated.
Therefore, to identify and evaluate potential mitigation strategy options, a second sensitivity analysis was performed. The impact of probabilistic inputs on the final concentration of G. stearothermophilus in plant-based milk alternatives, in case of contamination (prevalence artificially set to 100%) is presented in Fig. 3b. The variability related to the heat treatment has the highest impact (0. 87 95% CI (0. 86; 0. 88)) on the final concentration of G. stearothermophilus in the plant-based milk alternatives. As illustrated in the tornado plot, the uncertainty dimension is relatively narrow (0. 86; 0. 88). This small impact of the uncertainty included in the heat treatment can be explained by the large D-value dataset used for the fitting. The storage temperature during day at consumer stage (0.
In the same vein, the risk of spoilage estimated for the PBMA is notably higher compared to the risk of canned milk reported by  Koutsoumanis et al. (2022). However, the risk of spoilage of PBMA is relatively lower compared to the non-sterility incidences in canned green beans which was reported to reach 0. 5 %  (Rigaux et al. , 2014). The risk of spoilage due to the growth of G. stearothermophilus in PBMA transported and stored in North (Poland) and South Europe (Greece) under the current climatic conditions was estimated as the baseline scenario in this study. As expected, there is no risk of spoilage during wintertime for both countries since the recorded historical temperature data for 2022 did not exceed the minimum temperature of growth of G. stearothermophilus. On the contrary, current temperature conditions during summertime allowed growth in both countries.
, 2021 Optimum pH of growth pH opt - 6. 74 Eq. (19) fixed Misiou et al. , 2021 Maximum pH of growth pH max - 8. 71 Eq. (19) fixed Misiou et al. , 2021 pH of the product pH - 7. 00 Eq. (19) Assumption fixed Secondary cardinal pH model error sd3 - 0. 056 Eq. (20) U Misiou et al. , 2021 Temperature during distribution T tr • C Empirical distribution based on T Eq. (17) Data loggers dataset V Sup. data Time during distribution t tr h Uniform (2;12) Eq. (13) with Assumption V Eq. (21) Percentage of insulated trucks P truck - Uniform (0. 1;0. 5) Eq. (14) with Assumption V & U separated Temperature of the product storage-retail T r • C Below 25 Eq. (17) Assumption fixed Temperature of the product storage during the T d • C Empirical distribution based on T Eq. (17) with www. wunderground. com day at consumer place dataset V Temperature of the product storage during the T n • C Empirical distribution based on T Eq.
Origin of samples Biological samples from Reunion Island were originated from two different collections. The CARBO collection consisted of a prospective cohort of patients with arbovirus infections, registered on clinicaltrials. gov (NCT01099852). The CARBO was started by the University Hospital of La Martinique in 2010 and extended to include patients from Reunion in 2018. The other collection, DEMARE, was established as part of an epidemiological cross-sectional study conducted in 2019-2020. Both collections were approved by The French Committee for the Protection of Individuals. Written consent was obtained from all participants. Blood samples from the Seychelles were collected by the Ministry of health of the Seychelles during outbreaks between January 2015 and December 2016. Bloods were collected from viremic patients presenting one or several dengue symptoms including fever, myalgia, headache, asthenia and thrombocytopenia and without recent travel history.
Virus isolation Viral isolation assays were conducted by inoculating the DENV-1 PCR-positive sera from viremic patients onto Vero E6 cells monolayers. Cultures were checked every day. When cytopathic effects were observed, supernatants (passage 1) were collected by centrifugation and stored at -80°C. The presence of viral RNA was con rmed by RT-PCR, as above, and by titration of viral infectious particles using plaque-forming unit assay  (7). Sequencing and genomic analysis Genomic data were generated using either Oxford Nanopore Technologies (MinION) sequencing based on the amplicon tiling protocol, or Illumina shotgun sequencing, or by combining data from both sequencing platforms  (13). For Illumina sequencing, libraries were generated from 10 ng of cDNA using the Celero™ PCR Work ow with Enzymatic fragmentation (DNA-Seq) following the manufacturer's instructions.
Sequencing was performed on the MiSeq platform, with 1 * 170 bp single-end reads. Demultiplexed sequences were provided by the sequencing company (Bio dal, Lyon, France). Sequences were quality trimmed and adapters removed using Trimmomatic v0. 39  (14). Trimmed reads were mapped to reference sequence NC_001477. 1 using bowtie2. Geneious v9. 1. 8 (15)  was used to inspect and curate mapped sequence data. For Oxford Nanopore Technology's MinION sequencing, an amplicon tiling protocol was used in conjunction with DENV1 primers from the Oxford Centre for Arbovirus Discovery, Diagnostics, Genomics and Epidemiology (https://www. caddecentre. org/protocols/). Brie y, cDNA was ampli ed in two independent PCR reactions. PCR products were pooled, dA-tailed using the NEBNext® Ultra™ II End Repair/dA-Tailing Module then barcoded using the Nanopore Native Barcoding Expansion kit (EXP-NBD104).
Barcoded amplicons were then puri ed using a 0. 4x volume of AMPure-XP SPRI beads, washing the beads with an excess volume of Nanopore's small fragment buffer (SFB) to ensure that unligated barcode molecules were removed. Puri ed amplicons were then pooled in equimolar proportions before adapter ligation and sequencing, following the manufacturer's instructions. The sequencing run was left for 24 hours and stopped when predicted coverage exceeded 1000-fold for each genome. Basecalling and demultiplexing were performed using guppy (v4. 0. 11). Base-calling used default parameters in accurate mode, and demultiplexing was performed using the "require_barcodes_both_ends" parameter to minimize sample crosstalk. Reads were then assembled using Medaka v1. 0. 3 (https://nanoporetech. github. io/medaka/) mimicking the ARTIC network bioinformatics standard operating procedure for SARS-CoV-2 sequencing (https://artic.
Phylogenetic analysis Global phylogenetic comparisons were carried out using the E-gene, which is typically used for identifying dengue genotypes  (5). The E-gene region was extracted from all reference sequences in the NCBI database using custom scripts. Alignments were generated using MAFFT (16), and the alignment was curated by eye in Geneious v9. 1. 8. IQTree2 (v2. 1. 3) was used to identify optimal substitution model parameters and to generate a bootstrapped maximum-likelihood phylogeny with 1000 replicates. Phylogenetic tree representations were generated in R, using the "ggtree" package  (17).
Upon sequence inspection, mismatches were identi ed in the DENV1_3, DENV1_11 and DENV1_12 primer pairs which may explain ine cient ampli cation of DENV1 genotype V. Further optimization of the amplicon tiling protocol would be required to allow e cient ampli cation and sequencing of all DENV-1 genotypes by this method. *Genome coverage is considered complete for Illumina data if the sequence obtained mapped to more than 98% of the DENV-1 reference sequence (Genbank accession number NC_001477. 1). The amplicon tiling protocol for MinION used primer positions that did not amplify 155 bp at the 5' extremity, nor 575 bp at the 3' extremity of each genome, thus complete contiguous sequences using MinION map to 93% of the same reference sequence.
Phylogeny Phylogenetic analyses of the approximately 5000-bp genomic region of 3,891 publicly available sequences showed that all sequences from Reunion Island found in 2019, 2020 and 2021 belonged to genotype I of DENV-1 (Fig. 1a ), and possessed nearly identical sequences, forming a monophyletic cluster in the phylogeny. These sequences showed greatest similarity (99. 5% identity) to one isolate from Sri Lanka in 2020 (Accession number OL752439. 1) and two sequences from China in 2016 (Accession numbers MN933661 and MN933663). Sequences from the Seychelles belonged to the same major phylogenetic branch of DENV-1 genotype V, but fell into two paraphyletic clusters (Fig. 1a ). DS16177 showed greatest similarity (> 99% identity) to sequences from 2016-2017 isolated in Bangladesh, Singapore and China, whereas DS16229, DS16232, DS16233 and DS16243 showed greatest similarity to numerous ancestral isolates from Singapore, dating back to 2012.
More recently, dengue outbreaks due to DENV-2 occurred in 2016 in the Seychelles and then in 2018 in Reunion, and it was shown to involve the same cosmopolitan sub-lineage I (6,7). The presence of two distinct sub-lineages of DENV-1 in the Seychelles advocates for at least two introduction events. Conversely, despite the limited number of complete genome sequences of DENV-1 genotype I in databases, the phylogenomic tree (Additional le) strongly suggests a single introduction event in Reunion. In these two countries, DENV-1 displaced the previously circulating DENV-2. The displacement phenomenon was also reported among genotypes of the same dengue serotype. For instance, during the DENV-2 outbreaks in several South American countries, the American genotype was replaced by the Asian genotype  (21).
2. 2. 1 Primary outcomes: All-cause dementia and AD Data on primary outcomes were available in all cohorts. In The UK Biobank and The Tromsø studies, cases of incident dementia were identified via linkage to hospital episode statistics data (e. g. , death registry and hospital inpatient records in the UK Biobank) and classified using the International Classification of Diseases, ninth and tenth revision (ICD-9 and ICD-10). 11  In The Maastricht Study, potential cases of incident dementia were identified via hospital records. Medical data were checked by a geriatric specialist and dementia cases were diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. In The Alienor Study, potential cases of dementia were identified based on a neuropsychological test battery.
Retinal thickness indices The thickness of inner retinal layers (i. e. , mRNFL and mGCIPL) was assessed at the macula (peri-foveal) in both eyes with OCT. We calculated global mRNFL and mGCIPL thickness indices using data from both eyes (i. e. , we calculated the mean thickness of both eyes), or, if data were only available for one eye, using data from that eye only.
95% confidence interval [CI]). Follow-up time was calculated as the time between OCT measurement and censoring (the date of incident dementia, the date of death, or the last date at which data on dementia and death status were available). For analyses with individual types of dementia, we censored participants who developed other types of dementia than the type of dementia of interest. 15  We used the following models. In the crude model, we adjusted for cohort to account for differences in the assessment of variables between cohorts. In Model 1, we additionally adjusted for age, sex, educational level, and spherical equivalent, as these variables are key determinants of risk of dementia (age, sex, educational level [the latter is a proxy of social economic status])  2  or retinal thickness (spherical equivalent can affect the assessment of retinal thickness).
Additional analyses We performed a range of additional analyses. First, we analyzed associations in individual cohorts. Second, we analyzed the association of change in retinal thickness over time with incident dementia. Third, we repeated analyses after exclusion of individuals with eye diseases. Fourth, we analyzed the association of APOE genotype status with retinal thickness. Fifth, we performed competing risk analyses to account for risk of death. 21  Other analyses are reported in the Supporting Information. Main analyses were performed using Statistical Package for Social Sciences version 28. 0 (IBM SPSS, IBM Corp. ). For all analyses (including interaction analyses) a P-value < 0. 05 was considered statistically significant in two-sided tests.
ACKNOWLEDGMENTS The authors would like to acknowledge the  ZIO foundation  ( Vereniging Regionale HuisartsenZorg Heuvelland)  for their contribution to The Maastricht Study. The researchers are indebted to all participants for their willingness to participate in the study. The  UK Biobank : This research has been conducted using the  UK Biobank Resource  under application number  36741. Elżbieta Kuźma  was supported by the  Nicolaus and Margrit Langbehn Foundation. The  Tromsø Study : The  Tromsø Study  was funded by  UiT The Arctic University of Norway , The  North Norwegian Regional Health Authority , The  Norwegian Ministry of Health and Care Services , The  University Hospital of North Norway ,  Troms County ,  Jon S. Larsens   Foundation ,  HelseNord  (the  Regional Health Authorities in North Norway) , and the  Norwegian Foundation for Glaucoma Research.
Participants We used data from a pilot open-label study that we launched in 2017 to assess the safety and effectiveness of BTX/A ic as an add-on therapy for ED. The inclusion criteria were heterosexual men aged ≥18 years who had shown an insufficient response for at least 3 months to the registered PDE5-Is at the highest approved dose, either on-demand or daily (tadalafil), or to PGE1 ICIs with a dose up to 60 µg. Insufficient response to the pharmacological ED treatment was defined as an IIEF-EF domain score < 26 on treatment  [20]. BTX/A ic was performed as previously described  [14]. Briefly, an adjustable penile loop ring was placed at the penile crus for 30 mins. Then, two syringes with a 13 mm long 29 1 /2 G needle were used to deliver 0. 5 ml of BTX/A into each corpus cavernosum. For the current study, we included data from all men who had undergone at least two BTX/A ic injections.
Statistical analysis Characteristics of women and men were summarized as number (percentage) for categorical variables and as mean (standard deviation) for continuous variables, unless they had skewed distributions when median (interquartile interval) was used. Sex-specific Kaplan-Meier survival curves were constructed using the survminer R package to assess the dementia-free survival probability, and the log-rank test was performed to compare the difference between the two survival curves. Only age and education were available for all individuals. Missing values (Table  S14  in supporting information) were imputed using multiple imputation by chained equations (MICE), with 30 imputed datasets created using the mice R package in the pooled data from the 21 cohorts, 17 on all exposures, covariates, and study outcomes.
Different imputation methods were specified depending on the type of the variable (predictive mean matching ["pmm"] for numeric data, and logistic regression imputation ["logreg"] for binary data). The patterns of missingness were assessed using "md. pattern()" package in R. Cox proportional hazards models were applied to calculate age-and education-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) for sex as a RF (women vs. men) associated with the risk of allcause dementia in each study. A pooled estimate across all studies was calculated using a one-stage meta-analytical approach, combining the imputed individual participant data from 21 cohorts, using a Cox proportional hazards mixed effect model containing Gaussian random effects to take the study variability into account, using the R package coxme.
Sex differences in risk factor associations The current study found similar associations between most RFs and dementia risk in men and women, and there was only moderate evidence indicating that APOE ε4 carriage was more strongly associated with dementia risk in men than women in our diverse populations. In contrast, previous studies from the United States reported a stronger association between APOE ε4 and dementia risk for women than men. 49, 50 In our global dataset, we found no evidence indicating an effect modification by age or region, on the sex differences in the effect of APOE ε4 carriage on all-cause dementia. A previous meta-analysis of 27 independent studies, with data representative of non-Hispanic White individuals in North America and Europe, found that the effect of a single copy of APOE ε4 on Alzheimer's disease (AD) was similar for women and men.
12 Importantly, how early-life socioeconomic disadvantage is manifested in brain health later in life,  10  and how it interacts with cardiovascular RFs, and may be related to sex differences in dementia risk need to be better contextualized. Sex-specific RFs, including reproductive factors and the hormonal milieu, may also be pertinent in understanding the differential contributions to the sex-specific risk of dementia. 56 These should be considered when interpreting the findings from the current study, given that the women included are likely to be post-menopausal. A recent study using UK Biobank data also found several reproductive events related to shorter cumulative exposure to endogenous estrogen were linked to a greater risk of dementia. 46 Future studies with repeated measures of sex hormones, together with reliable documentation of sex-specific factors and exogenous hormone use through the life course would be necessary to understand their contributions to the sex-specific risk of dementia.
Group #19; A. L. received financial support to attend scientific meeting from Janssen. E. L. has received honorarium from University of Granada. None of these activities was related to the current project. M. W. is supported by Australian NHMRC and EU Horizon 2020, and is a consultant for Amgen and Freeline outside the submitted work; and participated on a Data Safety Monitoring Board or Advisory Board for DMB STAREE trial (no payment). The rest of the authors have no conflicts of interest. C. D. L. C. has received financial support to attend scientific meetings from Janssen, Almirall, Lilly, Lundbeck, Rovi, Esteve, Novartis, Astrazeneca, Pfizer, and Casen Recordati. M. W. has been a consultant for Amgen, Freeline, and Kirin outside the submitted work. Author disclosures are available in the supporting information.
Funding information UK Medical Research Council Skills Development Fellowship , Grant/Award Number:  MR/P014550/1 ;  Australian National Health and Medical Research Council   Investigator Grant, Grant/Award Numbers :  APP1174120 ,  APP1149987 ;  National Institute on Aging of the National Institutes of Health , Grant/Award Number:  RF1AG057531 ;  French National Research Agency , Grant/Award Numbers:  ANR-09-MNPS-009-01 , Grant  IIRG-09-133 , 014 ;  Alzheimer's Association , Grant/Award Number:  18910276/8/9/2011 ;  European Social Fund , Grant/Award Number:  ΔΥ2β/οικ0. 51657/14. 4. 2009; Ministry of Health and Social Solidarity ; JSPS  KAKENHI, Grant/Award Numbers :  JP17K09146 , ,  LRGS/BU/2012/UKM-UKM/K/01 ;  Fondo de Investigación Sanitaria, Instituto de Salud Carlos III ,  Spanish Ministry of Economy and Competitiveness , Grant/Award Numbers:  94/1562 ,  97/1321E ,  98/0103 ,  01/0255 ,  03/0815 ,  06/0617 ,  G03/128 ,  12/02254 ,  16/00896 ,  19/01874 ;  Fondo Europeo de Desarrollo Regional (FEDER) , Grant/Award Number:  B15_17R ;  NIH/NIA , Grant/Award Numbers:  AG03949 , # R37AG023651 ;  National Institute on Aging ;  ALF-agreement, Grant/Award Numbers :  ALF965812 ,  ALF 716681 ;  Swedish Research Council , Grant/Award Numbers:  11267 ,  2005-8460 ,  2007-7462 ,  2012-5041 ,  2015-02830 ,  2019-01096 ;  Swedish Research Council   RAM, Grant/Award Number :  2013-8717 ;  Swedish Research Council for Health ,  Working Life  and  Wellfare, Grant/Award Numbers :  2012-1138 ,  2013-1202 ,  2018-00471 ,  AGECAP 2013-2300 , no  2013-2496 ;  Hjärnfonden/Swedish Brain Foundation , Grant/Award Numbers:  FO2014-0207 ,  FO2016-0214 ,  FO2018-0214 ,  FO2019-0163 ,  FO2020-0235 ;  Alzheimerfonden, Grant/Award Numbers :  AF-554461 ,  AF-647651 ,  AF-743701 ,  AF-844671 ,  AF-930868 ,  AF940139 ,  AF-968441 ;  Alzheimer's Association Zenith Award , Grant/Award Number:  ZEN-01-3151.