This article describes a free, open-source collection of templates for the popular Excel (2013, and later versions) spreadsheet program. These templates are spreadsheet files that allow easy and intuitive learning and the implementation of practical examples concerning descriptive statistics, random variables, confidence intervals, and hypothesis testing. Although they are designed to be used with Excel, they can also be employed with other free spreadsheet programs (changing some particular formulas). Moreover, we exploit some possibilities of the ActiveX controls of the Excel Developer Menu to perform interactive Gaussian density charts. Finally, it is important to note that they can be often embedded in a web page, so it is not necessary to employ Excel software for their use. These templates have been designed as a useful tool to teach basic statistics and to carry out data analysis even when the students are not familiar with Excel. Additionally, they can be used as a complement to other analytical software packages. They aim to assist students in learning statistics, within an intuitive working environment. Supplementary materials with the Excel templates are available online.

To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.

Abstract

The harmonized data set on health, created and published by the ERF, is a subset of Iraq Household Socio Economic Survey (IHSES) 2012. It was derived from the household, individual and health modules, collected in the context of the above mentioned survey. The sample was then used to create a harmonized health survey, comparable with the Iraq Household Socio Economic Survey (IHSES) 2007 micro data set.

----> Overview of the Iraq Household Socio Economic Survey (IHSES) 2012:

Iraq is considered a leader in household expenditure and income surveys where the first was conducted in 1946 followed by surveys in 1954 and 1961. After the establishment of Central Statistical Organization, household expenditure and income surveys were carried out every 3-5 years in (1971/ 1972, 1976, 1979, 1984/ 1985, 1988, 1993, 2002 / 2007). Implementing the cooperation between CSO and WB, Central Statistical Organization (CSO) and Kurdistan Region Statistics Office (KRSO) launched fieldwork on IHSES on 1/1/2012. The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

The survey has six main objectives. These objectives are:

1. Provide data for poverty analysis and measurement and monitor, evaluate and update the implementation Poverty Reduction National Strategy issued in 2009.
2. Provide comprehensive data system to assess household social and economic conditions and prepare the indicators related to the human development.
3. Provide data that meet the needs and requirements of national accounts.
4. Provide detailed indicators on consumption expenditure that serve making decision related to production, consumption, export and import.
5. Provide detailed indicators on the sources of households and individuals income.
6. Provide data necessary for formulation of a new consumer price index number.

The raw survey data provided by the Statistical Office were then harmonized by the Economic Research Forum, to create a comparable version with the 2006/2007 Household Socio Economic Survey in Iraq. Harmonization at this stage only included unifying variables' names, labels and some definitions. See: Iraq 2007 & 2012- Variables Mapping & Availability Matrix.pdf provided in the external resources for further information on the mapping of the original variables on the harmonized ones, in addition to more indications on the variables' availability in both survey years and relevant comments.

Geographic coverage

National coverage: Covering a sample of urban, rural and metropolitan areas in all the governorates including those in Kurdistan Region.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

Kind of data

Sample survey data [ssd]

Sampling procedure

----> Design:

Sample size was (25488) household for the whole Iraq, 216 households for each district of 118 districts, 2832 clusters each of which includes 9 households distributed on districts and governorates for rural and urban.

----> Sample frame:

Listing and numbering results of 2009-2010 Population and Housing Survey were adopted in all the governorates including Kurdistan Region as a frame to select households, the sample was selected in two stages: Stage 1: Primary sampling unit (blocks) within each stratum (district) for urban and rural were systematically selected with probability proportional to size to reach 2832 units (cluster). Stage two: 9 households from each primary sampling unit were selected to create a cluster, thus the sample size of total survey clusters was 25488 households distributed on the governorates, 216 households in each district.

----> Sampling Stages:

In each district, the sample was selected in two stages: Stage 1: based on 2010 listing and numbering frame 24 sample points were selected within each stratum through systematic sampling with probability proportional to size, in addition to the implicit breakdown urban and rural and geographic breakdown (sub-district, quarter, street, county, village and block). Stage 2: Using households as secondary sampling units, 9 households were selected from each sample point using systematic equal probability sampling. Sampling frames of each stages can be developed based on 2010 building listing and numbering without updating household lists. In some small districts, random selection processes of primary sampling may lead to select less than 24 units therefore a sampling unit is selected more than once , the selection may reach two cluster or more from the same enumeration unit when it is necessary.

Mode of data collection

Face-to-face [f2f]

Research instrument

----> Preparation:

The questionnaire of 2006 survey was adopted in designing the questionnaire of 2012 survey on which many revisions were made. Two rounds of pre-test were carried out. Revision were made based on the feedback of field work team, World Bank consultants and others, other revisions were made before final version was implemented in a pilot survey in September 2011. After the pilot survey implemented, other revisions were made in based on the challenges and feedbacks emerged during the implementation to implement the final version in the actual survey.

----> Questionnaire Parts:

The questionnaire consists of four parts each with several sections: Part 1: Socio – Economic Data: - Section 1: Household Roster - Section 2: Emigration - Section 3: Food Rations - Section 4: housing - Section 5: education - Section 6: health - Section 7: Physical measurements - Section 8: job seeking and previous job

Part 2: Monthly, Quarterly and Annual Expenditures: - Section 9: Expenditures on Non – Food Commodities and Services (past 30 days). - Section 10 : Expenditures on Non – Food Commodities and Services (past 90 days). - Section 11: Expenditures on Non – Food Commodities and Services (past 12 months). - Section 12: Expenditures on Non-food Frequent Food Stuff and Commodities (7 days). - Section 12, Table 1: Meals Had Within the Residential Unit. - Section 12, table 2: Number of Persons Participate in the Meals within Household Expenditure Other Than its Members.

Part 3: Income and Other Data: - Section 13: Job - Section 14: paid jobs - Section 15: Agriculture, forestry and fishing - Section 16: Household non – agricultural projects - Section 17: Income from ownership and transfers - Section 18: Durable goods - Section 19: Loans, advances and subsidies - Section 20: Shocks and strategy of dealing in the households - Section 21: Time use - Section 22: Justice - Section 23: Satisfaction in life - Section 24: Food consumption during past 7 days

Part 4: Diary of Daily Expenditures: Diary of expenditure is an essential component of this survey. It is left at the household to record all the daily purchases such as expenditures on food and frequent non-food items such as gasoline, newspapers…etc. during 7 days. Two pages were allocated for recording the expenditures of each day, thus the roster will be consists of 14 pages.

Cleaning operations

----> Raw Data:

Data Editing and Processing: To ensure accuracy and consistency, the data were edited at the following stages: 1. Interviewer: Checks all answers on the household questionnaire, confirming that they are clear and correct. 2. Local Supervisor: Checks to make sure that questions has been correctly completed. 3. Statistical analysis: After exporting data files from excel to SPSS, the Statistical Analysis Unit uses program commands to identify irregular or non-logical values in addition to auditing some variables. 4. World Bank consultants in coordination with the CSO data management team: the World Bank technical consultants use additional programs in SPSS and STAT to examine and correct remaining inconsistencies within the data files. The software detects errors by analyzing questionnaire items according to the expected parameter for each variable.

----> Harmonized Data:

• The SPSS package is used to harmonize the Iraq Household Socio Economic Survey (IHSES) 2007 with Iraq Household Socio Economic Survey (IHSES) 2012.
• The harmonization process starts with raw data files received from the Statistical Office.
• A program is generated for each dataset to create harmonized variables.
• Data is saved on the household and individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

Iraq Household Socio Economic Survey (IHSES) reached a total of 25488 households. Number of households refused to response was 305, response rate was 98.6%. The highest interview rates were in Ninevah and Muthanna (100%) while the lowest rates were in Sulaimaniya (92%).

Excel Table providing the collected data, together with a Excel-based tool to extract specific parts of the data.

Abstract

The intention is to collect data for the calendar year 2009 (or the nearest year for which each business keeps its accounts. The survey is considered a one-off survey, although for accurate NAs, such a survey should be conducted at least every five years to enable regular updating of the ratios, etc., needed to adjust the ongoing indicator data (mainly VAGST) to NA concepts. The questionnaire will be drafted by FSD, largely following the previous BAS, updated to current accounting terminology where necessary. The questionnaire will be pilot tested, using some accountants who are likely to complete a number of the forms on behalf of their business clients, and a small sample of businesses. Consultations will also include Ministry of Finance, Ministry of Commerce, Industry and Labour, Central Bank of Samoa (CBS), Samoa Tourism Authority, Chamber of Commerce, and other business associations (hotels, retail, etc.).

The questionnaire will collect a number of items of information about the business ownership, locations at which it operates and each establishment for which detailed data can be provided (in the case of complex businesses), contact information, and other general information needed to clearly identify each unique business. The main body of the questionnaire will collect data on income and expenses, to enable value added to be derived accurately. The questionnaire will also collect data on capital formation, and will contain supplementary pages for relevant industries to collect volume of production data for selected commodities and to collect information to enable an estimate of value added generated by key tourism activities.

The principal user of the data will be FSD which will incorporate the survey data into benchmarks for the NA, mainly on the current published production measure of GDP. The information on capital formation and other relevant data will also be incorporated into the experimental estimates of expenditure on GDP. The supplementary data on volumes of production will be used by FSD to redevelop the industrial production index which has recently been transferred under the SBS from the CBS. The general information about the business ownership, etc., will be used to update the Business Register.

Outputs will be produced in a number of formats, including a printed report containing descriptive information of the survey design, data tables, and analysis of the results. The report will also be made available on the SBS website in “.pdf” format, and the tables will be available on the SBS website in excel tables. Data by region may also be produced, although at a higher level of aggregation than the national data. All data will be fully confidentialised, to protect the anonymity of all respondents. Consideration may also be made to provide, for selected analytical users, confidentialised unit record files (CURFs).

A high level of accuracy is needed because the principal purpose of the survey is to develop revised benchmarks for the NA. The initial plan was that the survey will be conducted as a stratified sample survey, with full enumeration of large establishments and a sample of the remainder.

Geographic coverage

National Coverage

Analysis unit

The main statistical unit to be used for the survey is the establishment. For simple businesses that undertake a single activity at a single location there is a one-to-one relationship between the establishment and the enterprise. For large and complex enterprises, however, it is desirable to separate each activity of an enterprise into establishments to provide the most detailed information possible for industrial analysis. The business register will need to be developed in such a way that records the links between establishments and their parent enterprises. The business register will be created from administrative records and may not have enough information to recognize all establishments of complex enterprises. Large businesses will be contacted prior to the survey post-out to determine if they have separate establishments. If so, the extended structure of the enterprise will be recorded on the business register and a questionnaire will be sent to the enterprise to be completed for each establishment.

SBS has decided to follow the New Zealand simplified version of its statistical units model for the 2009 BAS. Future surveys may consider location units and enterprise groups if they are found to be useful for statistical collections.

It should be noted that while establishment data may enable the derivation of detailed benchmark accounts, it may be necessary to aggregate up to enterprise level data for the benchmarks if the ongoing data used to extrapolate the benchmark forward (mainly VAGST) are only available at the enterprise level.

Universe

The BAS's covered all employing units, and excluded small non-employing units such as the market sellers. The surveys also excluded central government agencies engaged in public administration (ministries, public education and health, etc.). It only covers businesses that pay the VAGST. (Threshold SAT$75,000 and upwards).

Kind of data

Sample survey data [ssd]

Sampling procedure

-Total Sample Size was 1240 -Out of the 1240, 902 successfully completed the questionnaire. -The other remaining 338 either never responded or were omitted (some businesses were ommitted from the sample as they do not meet the requirement to be surveyed) -Selection was all employing units paying VAGST (Threshold SAT $75,000 upwards)

WILL CONFIRM LATER!!

OSO LE MEA E LE FAASA...AEA :-)

Mode of data collection

Mail Questionnaire [mail]

Research instrument

1. General instructions, authority for the survey, etc;
2. Business demography information on ownership, contact details, structure, etc.;
3. Employment;
4. Income;
5. Expenses;
6. Inventories;
7. Profit or loss and reconciliation to business accounts' profit and loss;
8. Fixed assets - purchases, disposals, book values
9. Thank you and signature of respondent.

Supplementary Pages Additional pages have been prepared to collect data for a limited range of industries. 1.Production data. To rebase and redevelop the Industrial Production Index (IPI), it is intended to collect volume of production information from a selection of large manufacturing businesses. The selection of businesses and products is critical to the usefulness of the IPI. The products must be homogeneous, and be of enough importance to the economy to justify collecting the data. Significance criteria should be established for the selection of products to include in the IPI, and the 2009 BAS provides an opportunity to collect benchmark data for a range of products known to be significant (based on information in the existing IPI, CPI weights, export data, etc.) as well as open questions for respondents to provide information on other significant products. 2.Tourism. There is a strong demand for estimates of tourism value added. To estimate tourism value added using the international standard Tourism Satellite Account methodology requires the use of an input-output table, which is beyond the capacity of SBS at present. However, some indicative estimates of the main parts of the economy influenced by tourism can be derived if the necessary data are collected. Tourism is a demand concept, based on defining tourists (the international standard includes both international and domestic tourists), what products are characteristically purchased by tourists, and which industries supply those products. Some questions targeted at those industries that have significant involvement with tourists (hotels, restaurants, transport and tour operators, vehicle hire, etc.), on how much of their income is sourced from tourism would provide valuable indicators of the size of the direct impact of tourism.

Cleaning operations

Partial imputation was done at the time of receipt of questionnaires, after follow-up procedures to obtain fully completed questionnaires have been followed. Imputation followed a process, i.e., apply ratios from responding units in the imputation cell to the partial data that was supplied. Procedures were established during the editing stage (a) to preserve the integrity of the questionnaires as supplied by respondents, and (b) to record all changes made to the questionnaires during editing. If SBS staff writes on the form, for example, this should only be done in red pen, to distinguish the alterations from the original information.

Additional edit checks were developed, including checking against external data at enterprise/establishment level. External data to be checked against include VAGST and SNPF for turnover and purchases, and salaries and wages and employment data respectively. Editing and imputation processes were undertaken by FSD using Excel.

Sampling error estimates

NOT APPLICABLE!!

The 1986 Census was the first mid-decade census to undertake detailed enumeration. Data on demographic, social and economic characteristics, as well as on dwellings, were collected from Canadians. The information is recorded on two data bases, the 100% data base and the 20% sample data base. The 100% data bases includes general demographic, dwelling and household data (for example: age, sex, marital status, mother tongue and structural type of dwelling) collected from the entire population. The 20% sample data base includes the general demographic data, detailed socio-economic data (for example: ethnic origin, labour force activity, schooling, income and dwellings information) collected from one-fifth of the population. The range of the 1986 Census products and services differs somewhat from the 1981 Census. The major changes are: A 40% reduction in the number of publications The replacement of the 1981 Census Summary Tapes program by the Basic Summary Cross-Tabulations Improvements in the Custom Tabulations Service The implementation of a new Semi-Custom product line Focus series is the aggregate statistics (multi-variate cross-tabulations) at census subdivision, census tract, and enumeration area levels. These 7 tables do not correspond to the print Focus series print publications. At present, EA-level tables are available on CD-ROM only.

Figures in scientific publications are critically important because they often show the data supporting key findings. Our systematic review of research articles published in top physiology journals (n = 703) suggests that, as scientists, we urgently need to change our practices for presenting continuous data in small sample size studies. Papers rarely included scatterplots, box plots, and histograms that allow readers to critically evaluate continuous data. Most papers presented continuous data in bar and line graphs. This is problematic, as many different data distributions can lead to the same bar or line graph. The full data may suggest different conclusions from the summary statistics. We recommend training investigators in data presentation, encouraging a more complete presentation of data, and changing journal editorial policies. Investigators can quickly make univariate scatterplots for small sample size studies using our Excel templates.

Excel spreadsheet containing, in separate sheets, the underlying data used for the statistical analysis and description of variables.

File List Supp1ExcelGuide.pdf Supp2ExcelCalculator.xls ExcelCalculatorAbundanceData.pdf ExcelCalculatorIncidenceData.pdf Description Supp1ExcelGuide.pdf contains a complete description of the variables and how to use the Excel Spreadsheet calculator. Supp2ExcelCalculator.xls is an Excel spreadsheet with formulas to calculate the statistics described in the paper.

Download Free Sample
This statistic denotes the global market size across several regions including North America, Europe, APAC, South America, and MEA. The medical transcription market size was estimated to be at USD 16.64 bn in 2020-2024.

The size of the global medical transcription market has been derived by triangulating data from multiple sources and approaches. While arriving at the market size, we have considered data points, such as the size of the parent market and the revenues of key market participants, such as Acusis LLC, Excel Transcriptions Inc., Global Medical Transcription LLC, iMedX Inc., Lingual Consultancy Services Pvt. Ltd., MModal IP LLC, MTBC Inc., nThrive Inc., Nuance Communications Inc., and World Wide Dictation Service of New York Inc.

Summary Trend TablesThe HCUP Summary Trend Tables include information on hospital utilization derived from the HCUP State Inpatient Databases (SID), State Emergency Department Databases (SEDD), National Inpatient Sample (NIS), and Nationwide Emergency Department Sample (NEDS). State statistics are displayed by discharge month and national and regional statistics are displayed by discharge quarter. Information on emergency department (ED) utilization is dependent on availability of HCUP data; not all HCUP Partners participate in the SEDD.The HCUP Summary Trend Tables include downloadable Microsoft® Excel tables with information on the following topics:Overview of trends in inpatient and emergency department utilizationAll inpatient encounter typesInpatient encounter typeNormal newbornsDeliveriesNon-elective inpatient stays, admitted through the EDNon-elective inpatient stays, not admitted through the EDElective inpatient staysInpatient service lineMaternal and neonatal conditionsMental health and substance use disordersInjuriesSurgeriesOther medical conditionsED treat-and-release visitsDescription of the data source, methodology, and clinical criteria (Excel file, 43 KB)Change log (Excel file, 65 KB)For each type of inpatient stay, there is an Excel file for the number of discharges, the percent of discharges, the average length of stay, the in-hospital mortality rate per 100 discharges,1 and the population-based rate per 100,000 population.2 Each Excel file contains State-specific, region-specific, and national statistics. For most files, trends begin in January 2017. Also included in each Excel file is a description of the HCUP databases and methodology.

Datasets Used in the GeoFusion R-CNN Study: validation set(.json/.jpg/*), geoscientific statistical results of samples (.excel), and outfall detection results (.shp)

Introduction Little is known about the consequences of the COVID-19 pandemic on the life of university students in Sub Saharan Africa (SSA). The objective of this study was to evaluate the socioeconomic and academic consequences of the COVID-19 pandemic on medical students studying at the University of Rwanda. Methods This was a cross-sectional study. An online survey using google form was sent to medical students in clinical training (year 3 till year 5) using convenience sampling followed by snowball sampling method. We collected data on participants’ demographics, general knowledge on the COVID-19 pandemic and perception on mitigation measures, and socio-economic and academic consequences of the COVID-19 pandemic. Descriptive statistics were used in excel 2015 software to calculate participants’ responses and categorical data were presented using frequencies and percentages. Results A total 187 participants completed the survey. Most participants described disruption in routine activities (72.7%), reduced travelling (69%), church closing (64.2%), and loss of freedom (57.2%) as examples of negative social consequences. While financial uncertainty (64.7%), decrease in income (49.7%), and increase in poverty rate (42.2%) were the main economic consequences. Issues with academic progress (95.7%), limited social life (56.1%), and repeating the year (42.8%) were examples of negative academic consequences. Conclusion The results of this study suggest that the COVID-19 had a negative social, economic, and academic consequences on medical students at the University of Rwanda. These finding may guide the design of interventions to mitigate the consequences of COVID-19 and to protect medical students against future pandemics and crises.

Additional file 1. Alignment statistics. Excel spreadsheets showing detailed calculations of alignment statistics.

Background: Facebook addiction is said to occur when an individual spends an excessive amount of time on Facebook, disrupting one’s daily activities and social life. The present study aimed to find out the level of Facebook addiction in the Nepalese context and briefly discuss the crimes associated with its unintended use. Methods: A descriptive cross-sectional study was conducted in the Department of Forensic Medicine of Lumbini Medical College. The study instrument was the Bergen Facebook Addiction Scale typed into a Google Form and sent randomly to Facebook contacts of the authors. The responses were downloaded in a Microsoft Excel spreadsheet and analyzed using Statistical Package for Social Sciences version 16. Results: The study consisted of 103 Nepalese participants, of which 54 (52.42%) were males and 49 females (47.58%). There were 11 participants (10.68%) who had more than one Facebook account. When different approaches were applied it was observed that 8.73% (n=9) to 39.80% (...

We present the LipidQuant 1.0 tool for automated data processing workflows in lipidomic quantitation based on lipid class separation coupled with high-resolution mass spectrometry. Lipid class separation workflows, such as hydrophilic interaction liquid chromatography or supercritical fluid chromatography, should be preferred in lipidomic quantitation due to the coionization of lipid class internal standards with analytes from the same class. The individual steps in the LipidQuant workflow are explained, including lipid identification, quantitation, isotopic correction, and reporting results. We show the application of LipidQuant data processing to a small cohort of human serum samples.

Methods Chemicals and lipid standards

Chemicals and solvents (LC/MS grade, Chromasolv-Honeywell, Riedel-de Haën, Germany) were purchased from Sigma Aldrich (St. Louis, MI, USA) or Merck (Darmstadt, Germany). The following nonendogenous lipids were purchased from Avanti Polar Lipids (Alabaster, AL, USA) or Nu-Chek Prep (Elysian, MN, USA) and used as internal standards (IS) for the quantitative analysis: MG 19:1/0:0/0:0, DG 12:1/0:0/12:1, TG 19:1/19:1/19:1, D7-CE 16:0, Cer d18:1/12:0, D7-cholesterol, LPC 17:0/0:0, LPE 14:0/0:0, PC 14:0/14:0, PE 14:0/14:0, SM d18:1/12:0, PS 14:0/14:0, PA 14:0/14:0, PG 14:0/14:0, LPG 14:0/0:0, HexCer d18:1/12:0, Hex2Cer d18:1/12:0, and SHexCer d18:1/12:0. Carbon dioxide (scCO2) with 99.995% purity was purchased from Messer (Bad Soden, Germany).

Samples

Human serum samples were isolated from the whole blood, drawn into tubes without anticoagulant (Sarstedt S-Monovette, Germany), incubated at room temperature for 60 min, centrifuged at 1500 × g for 15 min, the supernatant was transferred to Eppendorf tubes, and immediately frozen at ‑80°C until the extraction. The study was approved by the institutional ethical committee. All donors signed the informed consent. In total, 43 samples from female donors with an average age of 47 years and 22 samples of male donors with the average age of 44 years were investigated. The QC sample was a pooled sample from all serum samples.

Internal standard mixture

Stock solutions of all IS in the range of 0.25 to 2.1 µg/µL were prepared and mixed to obtain an IS mixture for spiking. The final concentrations of IS were reported in Table 1 in nmol/mL serum.

Table 1. Concentrations of IS for individual lipid classes

Extraction

A modified Folch procedure was used for lipid extraction. Human serum (25 µL), and the mixture of IS (17.5 µL) were homogenized in 3 mL of chloroform - methanol (2:1, v/v) for 10 min in an ultrasonic bath (40°C). When the samples reached ambient temperature, 600 µL of water were added, and the mixture was vortexed for 1 min. After 3 min of centrifugation (3000 rpm), the aqueous layer was removed, and the organic layer was evaporated under a gentle stream of nitrogen. The residue was dissolved in a mixture of 500 µL of chloroform - 2-propanol (1:1, v/v), carefully vortexed, and filtered (0.2 µm syringe filter). The extract was diluted 1:20 with the mixture of hexane - 2-propanol - chloroform (7:1.5:1.5, v/v/v) for ultrahigh-performance supercritical fluid chromatography – mass spectrometry (UHPSFC/MS) analysis.

Analysis

UHPSFC/MS measurements were carried out on an Acquity Ultra Performance Convergence Chromatography (UPC2) system hyphenated to the hybrid quadrupole - traveling wave ion mobility time-of-flight mass spectrometer Synapt G2 Si from Waters by using the commercial interface kit (Waters, Milford, MA, USA). The instrumental setting was the same as in the previous works (Lísa et al., 2015; Lísa et al., 2017). The lipid class separation was achieved by employing a Viridis BEH column (Waters, 100 x 3 mm, 1.7 µm) and the gradient elution. The mobile phase A was scCO2, and the mobile phase B and make-up solvent were MeOH with 1% water and 30 mM NH4OAc. The linear gradient was employed: 0 min - 1% B, 5 min - 51 % B, 6.5 min - 51% B, 6.8 min - 1% B. The total run time was 7.5 min. The column temperature was 60°C, the automatic back-pressure regulator was set to 1800 psi, the flow rate to 1.9 mL/min, the injection volume to 1 µL, and the make-up flow rate to 0.25 mL/min. Electrospray ionization in the positive-ion mode was used, and the mass range was set to m/z 50-1200 in the sensitivity mode. The continuum mode with a scan rate of 0.15 s was used for the analysis. The peptide leucine enkephalin was used as the lock mass with the scan time of 0.1 s and the interval of 30 s. The lock mass was scanned but not automatically applied for mass calibration correction. All samples were measured in duplicate.

Data processing

The noise reduction was performed on the raw files after measurements using the Waters compression tool. Afterwards, the files were lock mass corrected and converted into centroid data using the exact mass measure tool from Waters. Retention time ranges or mass scan ranges of individual lipid classes were determined by comparing the first and last measured samples to verify that the lipid class peak was still within the determined range even in case of possible retention time shifts. For each lipid class, the combined mass scan range of each lipid class was prepared by MarkerLynx XS (Waters). The peak separation window was 0.05 Da, and the intensity threshold was 3000 counts. Each method was applied for all quantified lipid classes in all samples within the sequence to obtain a summary table containing all features within the defined m/z range together with intensities for all samples in MarkerLynx XS. These tables obtained for each lipid class were exported as txt file and further processed by LipidQuant 1.0. The similar protocol may be used for data measured by mass spectrometers from other manufacturers to obtain the final txt file suitable for LipidQuant 1.0 processing.

Statistical analysis and visualization

SIMCA software, version 13.0 (Umetrics, Umeå, Sweden) was used to perform unsupervised principal component analysis (PCA) and supervised orthogonal projections to latent structures discriminant analysis (OPLS-DA). The scatter plots of the first and second components are shown for PCA. OPLS-DA separates samples into predefined classes, i.e., gender. The results table from LipidQuant 1.0 was copied into the SIMCA software, the studied lipids were defined as variables, and samples were defined as different observations. The data were pretreated by logarithmic transformation, centering, Pareto scaling, and evaluation of outliers. The logarithmic transformation aims to convert each lipid species into a Gaussian distribution. The centering relates the relative changes of lipid species to the average, where the Pareto scaling compensates the concentration differences of lipid species. The scaling allows that low abundant species contribute to the model to the same extent by dividing the centered species by the root of the standard deviation (Pareto scaling). To evaluate lipids of statistical relevance, a two-sided two sample T-test assuming unequal variances (Welch test) was performed for female and male samples in Microsoft Excel. P‑values <0.05 were considered to indicate statistical significance. For better visualization of differences in lipid concentrations between males and females, the S-plot was generated from the OPLS-DA plot (in SIMCA), box plots were constructed in R free software environment (https://www.r-project.org) using readxl and ggplot2 packages and diagram types from Microsoft Excel.

HPV self-sampling has the potential to improve early detection of cervical cancer among women living with HIV (WLHIV), but its acceptability varies, creating implementation challenges, especially in sub-Saharan Africa. This study aims to assess the acceptability of HPV self-sampling among WLHIV. We searched PubMed, Web of Science, CINAHL, Academic Medical Ultimate, Cochrane databases, and Google Scholar. The review protocol was registered with PROSPERO (CRD42022299781). Inclusion criteria were based on population, intervention, comparison, and outcome. Statistical analysis was done with R Studio version 4.3.2, and data abstraction was performed in Microsoft Excel. The analysis included 14 studies on the acceptability of HPV self-sampling among WLHIV. The overall acceptability rate was 73%. The pooled data showed that 94% felt comfortable with self-sampling, 72% found it easy to use, 10% reported pain, 14% felt embarrassed, and 41% felt confident about the process. The study found that a majority of WLHIV accepted HPV self-sampling, a higher rate than in the general female population. Many participants had concerns about the method’s efficacy. This indicates that while WLHIV generally views self-sampling positively, additional education and support are needed to improve their confidence in its accuracy and reliability.

Raw data and descriptive statistic data of the market survey performed with the Add-In XLSTAT 2009.1.02 is provided as Excel-file (CSV). The data include file name, sample name, area, calculated N2O amounts, test result and statistical values.

Excel sheets containing all data used for statistical analysis (right sheet) and the codebook (left sheet).