dataesr/scientific-paragraphs-categorization huggingface dataset:
Assessment Assessment was performed at baseline and each month by a trained neurologist with a face-to-face interview using the file that allowed to prospectively collect data in the FHU InovPain registry. This file included a headache diary filled in prospectively to assess: i) the monthly number of headache days (MHD); ii) the monthly number of migraine days (MMD) (defined as a day with a headache meeting the ICHD-3 C and D criteria for migraine without aura, or a day with a symptomatology meeting the ICHD-3 B and C criteria for migraine with aura, or one day with a headache considered by the patient to be migraine at onset and relieved by taking a specific migraine medication) and iii) the monthly number of days with acute treatment and/or symptomatic headache treatment used to assess the presence of medication overuse (MO) defined according to ICHD-3 criteria: ≥ 10 days per month of consumption for triptans, opioids and drug combinations; ≥ 15 days per month of consumption for paracetamol, aspirin and non-steroidal anti-inflammatory drugs.
This file also included various questionnaires patient-reported outcome (PRO) measures such as the HAD scale to assess emotional impairment (anxiety and depression), the HIT-6 scale to assess impact, the EQ5-D scale to assess health status and the Patient Global Impression of Change (PGIC). For this study, the data considered were: i) MHD and MMD in the month preceding the first administration of erenumab and then each month for one year (or until study discontinuation for patients not receiving one year's treatment) in order to establish the mean MHD and MMD at baseline (M0) and at 3 (M3), 6 (M6), 9 (M9) and 12 (M12) months following the first erenumab administration; ii) migraine form (high frequency episodic migraine [HFEM] or chronic migraine [CM]) at baseline (M0) and at 3 (M3), 6 (M6), 9 (M9) and 12 (M12) months following the first erenumab administration; iii) presence or absence of MO before the first administration of erenumab (M0) and at 3 (M3), 6 (M6), 9 (M9) and 12 (M12) months following this first administration; iv) HAD anxiety score and HAD depression score before the first administration of erenumab (M0); v) EQ-5 index before the first administration of erenumab (M0); vi) HIT-6 score before the first administration of erenumab (M0) and at 3 (M3), 6 (M6), 9 (M9) and 12 (M12) months following this first administration; vii) PGIC score at 3 (M3), 6 (M6), 9 (M9) and 12 (M12) months following the first administration of erenumab.
Statistics The study's sample size was not calculated based on statistical considerations. All consecutive adult patients included in the FHU InovPain registry who participated to the compassionate erenumab use program set up by Novartis Pharma SAS from April 2019 to September 2021 were included. The data were described using the mean and standard deviation [SD] or median interquartile range [IQR] for quantitative variables and the frequency and percentage for qualitative variables. To address the primary endpoint, the 50% responder rate was studied. Data at M6, M9 and M12 were compared with those obtained at M3 using McNemar tests. As 3 comparisons were performed for each measure, a p-value < 0. 016 (0. 05/3) was considered as significant. Data collected at baseline (age, gender, MMD, MHD, migraine form, MO, HAD A, HAD D, EQ-5D, HIT-6, psychiatric comorbidities, others comorbidities, tripan responsiveness) were tested using univariate analysis to determine if they were significantly related to the 50% responder rate at M3, M6, M9 and M12.
Ethics / regulations This observational study did not require the authorization of an ethics committee. This study was part of the FHU InovPain registry clinical research program which received authorization from the National Commission on Informatics and Liberty (Commission Nationale de l'Information et des Libertés-CNIL / CIL register no. 278 dated 11/09/2017). Patients were included only after signing two separate written informed consents: a first one enabling their personal data to be transmitted to Novartis Pharma SAS to validate their eligibility in the compassionate program allowing them to benefit from free erenumab and a second allowing the data collected in the FHU InovPain registry database to be used for clinical research purposes. The study was performed according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines  [8].
Discussion A number of real-world studies of migraine treatment with CGRP-mAbs have been published with a majority of studies on erenumab which was the first to obtain approval for migraine prevention  [9, 10]. These studies are characterized by a significant methodological heterogeneity  [11]  and interpretation of their results could be hampered by retrospective data collection, small patient numbers, and short follow-up periods. Nevertheless, some prospective studies, with at least one year's followup in more than 100 patients, support meaningful effectiveness and safety of erenumab in real-world patient populations including patients with CM, patients with MO and patients with multiple preventive treatment failures  [12] [13] [14] [15]. In this one year-prospective clinical-based study, we examined the effectiveness and safety of erenumab in a sample of 140 French adult migraine sufferers included in the FHU InovPain regstry and who participated in a compassionate use program.
Such a good safety profile of CGRP-mAbs during pregnancy is suggested by an analysis of the World Health Organization pharmacovigilance database performed by Noseda et al. that found no specific maternal toxicicty, patterns of major birth defects or increased reporting of spontaneous abortion  [25]. However, because of the relatively limited number of adverse drug reaction reported and the lack of long-term safety studies, CGRP-mAbs use should be avoided for migraine prevention in pregnant women. Further, the potential risk related to an unplanned pregnancy needs to be discussed with women of childbearing age before starting CGRP-mAb treatment  [26]. The findings of the present study confirm, in real-world settings, the favorable benefit/risk of erenumab already supported by a 'likehood of being helped or harmed' analysis using data of erenumab randomized clinical trials  [27].
Data Collection Upon enrollment and at months 3, 6, and 12, participants will be asked to complete a structured survey administered by a CHW. The survey will include questions regarding network size for RDS weighting. These will include questions about the token given at the time of data capture. Individual data including sociodemographic characteristics; sexual practices; knowledge and behavior; HIV testing history; medical history; PrEP knowledge, adherence, and compliance; contraception; drug and alcohol use; mental health (including Perceived Stress Scale-10 scores); quality of life; literacy; social support; being subjected to racism; stigmatization or violence during the past 12 months; and mobility will be collected. Other more structural determinants will be collected as follows: residence permits, health insurance, housing conditions, and food security (Table  1 ).
Data Analysis Descriptive statistics will be applied to the characteristics of the survey population. Categorical variables will be reported as percentages and compared using the chi-square test (and the Fisher exact test for small numbers). Continuous variables will be expressed as mean (SD) or median (IQR) values, and compared using Student and Wilcoxon signed ranked tests in accordance with the variable distribution. A simple logistic regression analysis will be applied to select variables associated with the outcome, and all variables with a P value of <. 10 will be entered into a multiple logistic regression model for each outcome. Statistical analysis will be performed using STATA Planned dissemination of study findings includes manuscript publication, conference presentations, and community dissemination (eg, community meetings and social network).
Acknowledgments The authors thank all participants, the operational team, and NGOs and especially Prospective Coopération,  AIDES , and The Truth for their support and help. The authors also want to thank  Ms. Sophie Gisclard  for her photographs use here as a Table of Contents image. This work was supported by  Sidaction  (grant  2020-2-AEQ-12890 ), by  ViiV HEALTHCARE , and by the  Marseille city.
Setting and Study Design This study was conducted to analyze the incidence and risk factors for VAP in COVID-19 patients during the first year of the pandemic in Marseille, France. A retrospective analysis of prospectively collected data of 248 adult patients with severe COVID-19 admitted to seven ICUs of three tertiary public hospitals between March 2020 and November 2020 was performed. A number of 87 patients who were never exposed to invasive mechanical ventilation were excluded, leaving 161 mechanically ventilated patients left as our final cohort. We then distinguished 82 patients who developed at least one VAP during their ICU stay and proceeded to describe the incidence and characteristics of this group. The remaining 79 patients were used as a control group (Figure  1 ). The participating centers shared comparable preventive care regarding hospital acquired infections including VAP.
Collected Data The following patient data were collected at admission: age, sex, body mass index (BMI), comorbidities including diabetes, hypertension, cardiovascular disease, metabolic syndrome, active smoking, chronic lung disease, chronic kidney disease and immunocompromised status. Patient characteristics at ICU admission included severity scores, PaO 2 /FiO 2 ratio and biological inflammation markers. Three critical patient severity scores were collected and are listed as follows: "Index de Gravité Simplifié 2" (IGS 2), Charlson and ROX. These complementary scores describe patient gravity, estimating predicted inhospital mortality for the first two using patient characteristics within the first 24 h of ICU admission and patient comorbidities respectively. The ROX score is a tool predicting high-flow nasal cannula failure and the need for mechanical ventilation.
Regarding neuroendocrine tumours (NET), we lack robust evidence that sex is a determinant in the prognosis or the effectiveness of treatments. There are no specific prospective studies in this area, and the available information is based mainly on retrospective cohorts. Large datasets of clinical trials have been analysed to determine sex differences in adverse events (AE). Unger JM et al. reviewed more than 23,000 patients included in 202 oncology clinical trials with systemic treatments and found a 66% increased risk of symptomatic AE and 34% of severe AE, specially in those treated with immunotherapy  [3]. Treatment with multikinase inhibitors (MKI) is an emerging therapy in the field of NET. Currently, only Sunitinib has a phase 3 randomised clinical trial in the Western population and is widely used in clinical practice  [4].
Statistical analysis The main objective was to determine if there were differences between toxicities affecting male and female patients in each trial. Therefore, we applied a test for proportions comparing the prevalence of each toxicity by sex. The pvalues and proportions with their 95% confidence intervals (CIs) by sex for each toxicity were reported. Second, we analysed which toxicities were different by sex considering all the trials together. Thus, we performed a pooled analysis with the disaggregated toxicity data for all the trials. We applied a logistic generalised linear mixed model with sex as response variable, each toxicity as the explanatory variable, and each trial as the random effect variable. Odds ratios (ORs) with 95% CIs, standard deviations of the random effect, and p-values were reported.
Discussion We collected sex-related toxicities in five clinical trials in NET patients treated with MKI. These trials collected and published combined toxicity data following usual practice in biomedical publications. We performed a pooled analysis to identify differential toxicities between female and male patients. We found nine toxicities more frequent in female patients (leukopenia, alopecia, vomiting, headache, bleeding, nausea, dysgeusia, neutrophil count decreased and dry mouth) and two toxicities more frequent in male patients (anal symptoms, insomnia). Also, we found a trend for aphonia to be more frequent in men. Asthenia and neutrophil count decrease were the two toxicities Grade 3/4 more frequent in female patients. The study of sex differences in medicine is a growing field and examines how diseases differ between males and females in terms of prevention, diagnosis, and treatment outcomes  [12].
In an analysis of The Surveillance, Epidemiology and End Results (SEER) database, female patients were more likely to have primary NET in lung, stomach, appendix, or caecum. Also, female patients were less likely to have metastasis at the onset  [17]  and better survival rates in lung  [18]  and GEP NET  [19, 20]. However, since these are population approaches, the impact of these findings into prevention and treatment remains unknown. Most clinical trials in the NET field were not specifically designed to investigate sex-related differences. Usually, this item is explored as covariate, with the perception that a lack of sex-adjustment in clinical practice is necessary. Current data is too heterogeneous to address conclusions which will impact in the therapeutic schedule. In recent years, individual efforts in some centres are reviewing the impact of sex in treatment outcomes with NET, but literature is still scarce.
The inclusion of gender information, beyond sex, in biomedical studies could help us determine the impact of this variable in future projects. Additionally, the  female; M: male. Odds ratio values over 1. 00 means the toxicity is higher in male versus female patients. Fig. 2. Significant differential toxicities between male and female patients after random effect ponderation between trials. heterogeneity in the report of adverse effects between trials increases the difficulty of exploring differential transversal toxicities according to sex. Another important limitation of the present study is the impossibility of accessing the complete datasets of all clinical trials that preclude a multivariate study and the impact of sex-related toxicities in efficacy outcomes. Although variability between trials was addressed by random effect, the impact of other characteristics such as body surface, comorbidities, general performance status, prior therapies, compliance and age, among others, must be considered.
9%) ORR 9. 4% Asthenia (65. 9%) (EudraCT 2008-000225-19) 200 mg bid d1-5 Gastrointestinal (31) mPFS 12. 4 HFS (61. 4%) + Mucositis (52. 3%) Bevacizumab Diarrhoea (50%) 5 mg/kg/2 w Hypertension (50%) Dysphonia (40. 9%) Anorexia (36. 4%) Arthralgia (22. 7%) Epistaxis (22. 7%) Cutaneous rash (18. 2%) PAZONET (4) Pazopanib Pancreatic (18) 20 (45. 5%) ORR 9% Asthenia (84. 1%) (NCT01280201) 800 mg/d Gastrointestinal (15) mPFS 9. 5 Diarrhoea (68. 2%) Other (11) Abdominal pain (52. 3%) Pain (47. 7%) Nausea (40. 9%) Hypertension (40. 9%) Hepatotoxicity (36. 4%) Vomiting (34. 1%) HFS (29. 5%) Mucositis (29. 5%) TALENT (5) Lenvatinib Pancreatic (55) 31 (56. 4%) ORR 44. 2% Asthenia (74. 8%) (NCT02678780) 24 mg/d Gastrointestinal (56) 23 (41. 1%) mPFS 15. 6 Diarrhoea (58. 6%) ORR 16. 4% Hypertension (55.
Based on this concept, we hypothesized that the regulation of these mechanisms early after damage could be a key determinant for cell fate decision. Using publicly available datasets, we compared the expression of genes involved in regulating oxidative stress-induced cell death in different types of senescent cells. Interestingly, we identi ed PARP1 as the most consistently downregulated gene during senescence (Extended Data Fig. 1a ). We experimentally validated this nding, and observed PARP1 downregulation at both the transcript and the protein level in senescent human broblasts (Extended Data Fig. 1b-c ). In accordance, senescent cells showed lower induction of PARP activity and higher resistance to lethal doses of H 2 O 2 (Extended Data Fig. 1d-e ), strongly suggesting that PARP signaling might be a key mediator in the decision between survival/senescence and death.
Senescence-Associated β-Galactosidase This protocol was accomplished according to Campisi et al  (32). Brie y, cells were washed in PBS buffer, xed for 3-5 min (room temperature) in 2% formaldehyde/ 0. 2% glutaraldehyde, washed, and then incubated with fresh senescence-associated β -Gal staining solution prepared as previously described and incubated at 37°C without CO2  (32). Images were acquired using Leica microscope and were processed using ImageJ software.
Comet assay Cells were incubated with vehicle or PJ34 followed by H 2 O 2 treatment (1mM) for 30 min. Cells were then trypsinized and analyzed for alkaline comet assay as previously described  (33). Brie y, cells were embedded in agarose on slides and incubated overnight at 4°C in lysis buffer. After that, the slides were incubated for 30 minutes in an alkaline electrophoresis buffer to denature and relax DNA before electrophoresis at 300 mA for 30 minutes. Following electrophoresis, slides were neutralized with 0. 4 M Tris buffer, submerged in 70% ethanol for 5 minutes, and stained with a DNA dye. Images were acquired using Leica microscope and were analyzed using CometScore 2. 0 software.
Measurement of mitochondrial membrane potential Mitochondrial membrane potential was measured as previously described  (34). Brie y, cells were pre-treated with vehicle or PJ34 and then incubated with TMRE (tetramethylrhodamine ethyl ester perchlorate, MedchemExpress, HY-D0985A) in modi ed Kreb's Ringer buffer for 30 min at 37°C. Then, cells were imaged using Delta Vision Elite imaging station (Applied Precision, GE Healthcare) and treated or not with H 2 O 2. Images were taken every 3 minutes using the 40x objective and processed using ImageJ software.
Public datasets analysis To pro le the cell death associated gene expression in different senescent programs, a gene set was downloaded from the MSigDB database with the GO release 2021-12-15 (http://www. gseamsigdb. org/gsea/emsigdb/cards/GOBP_REGULATION_OF_OXIDATIVE_STRESS_INDUCED_CELL_DEATH. html). Data sets for differential gene expression in six senescent models were downloaded from previously published data  (35). accession number GSE130727. Representative images of cells status were taken before measuring viability. Cell survival was measured by using an MTS assay.
Phylogenetic analyses Overlapping sequences were assembled into contiguous sequences using Geneious software package V. 2021. 2. 2 (Biomatters Ltd, Auckland, New Zealand). Partial non-concatenated nucleic acid sequences of the new Astrovirus were aligned using MEGA 7  [29]  , with minor manual adjustments. Sites that could not be unambiguously aligned and divergent regions were excluded from subsequent analyses. Phylogenies were inferred using Maximum Likelihood (ML) method implemented in PhyML  [30]. The suited evolution model was selected by Akaike's Information criterion (AIC) using Topali software  [31]. The reliability of branching orders was tested using the bootstrap approach (1000 replicates)  [32]  and the GTR + F+ I substitution model was determined as the best suited evolution model.
Two sequences isolated from Magweto cave, 1 from Rhinolophus spp (MAG-573) and 1 from Hipposideros spp (MAG-292) clustered with a group of Human astroviruses (HuAstVs) (Figure  4 ). This cluster was well sustained (Bootstrap >90%) and the nucleotidic acid identities between Bat Astroviruses MAG-573, MAG-292 and HuAstV-2 were 96 and 93% respectively (Data not shown). The other specific cluster of bat astrovirus showing a close relation to human astroviruses, is a sequence isolated from Hipposideros spp (MAG-1236) in Magweto, it clustered with HuAstV-MLB-1; -2 and 3 (Figure  4 ). Six sequences isolated from the frugivorous bats E. helvum found in Honde Valley and one from Rhinolophus spp collected in a Baobab tree formed a sister clade with another group of Human astroviruses HuAstV-VA-1;-2;-3;-4 and HuAstV-HMO-A (Figure  4 ).
Acknowledgments: We thank  Billy Butete  for his field assistance. The authors gratefully acknowledge and thank the  International Atomic Energy Agency  for making available the sequencing services. We thank the  Research Council of Zimbabwe  for approving this study (research registration certificate N° 03006) and the  Hurungwe Rural District council  for their assistance and facilitation. We thank the  Animal Research Ethics   Committee of Zimbabwe  for their approval (ref number  002/2017 ). This work was conducted within the framework of the  Research Platform "Production and Conservation in Partnership " ( RP-PCP ).
Study design and setting In this single-center retrospective cohort study, we reviewed the medical records of solid-organ transplant patients admitted to the infectious diseases department at the Bichat Claude Bernard University Hospital, Paris, France, between October 2017 and March 2019. Only those admitted for an infectious etiology were included in this study. No pediatric patient was admitted to this department. Transplant patients admitted to other departments of the hospital were not analyzed. This study was approved by the "Comited'Ethique de la Recherche (CER) Paris Nord" (Institutional Review Board -IRB 00006477-of HUPNVS, Paris 7 University, AP-HP). All patients received oral information from the referring physician at the time of consultation and provided their oral informed consent for data collection (between February and August 2022).
Data collection We extracted the following anonymous data from Orbis (Electronic medical records): demographic variables, comorbidities, type of organ transplantation, immunosuppressive drugs, clinical presentation at admission including fever, chills and symptoms and type of infection at admission, isolated pathogens, antibiotic /antiviral /antifungal treatment used and its duration, patients' outcome, intensive care unit (ICU) admission, and type of complications. Only deidentified /coded data were exported from Orbis for analysis. Data were inserted in a standardized form for statistical analysis. Each admission to the hospital was counted as a separate entity which allowed the inclusion of the same patient several times.
Statistical analysis Statistical analysis was performed using SPSS software. The normally distributed variables were expressed as means (±standard deviation) and compared with Student t-test. When the normal distribution condition was not respected, data were presented as medians (interquartile range), and compared with Mann-Whitney U Test. Categorical variables were expressed as numbers and percentages, compared using χ2 test with considering p values of 0. 05 or less as statistically significant. Then, we used logistic regression to identify risk factors associated with early and late period infection, death and ICU admission. Statistically significant factors as well as factors with a p-value between 0. 05 and 0. 25 were included in the binary logistic regression model to determine the independent predictive factors.