The Mothers' Milk Tool was developed to make more visible the economic value contributed to society by women's unpaid care work through breastfeeding infants and young children. This manuscript describes the development and display key features of the tool, and reports results for selected countries. For the development, we used five steps: (1) defining the tool by reviewing existing tools and scholarly literature to identify uses, approaches, design features, and required data characteristics for a suitable product; (2) specifying the best open-access data available for measurement and easy updating; (3) analyzing development options; (4) testing predictive models to fill identified breastfeeding data gaps; and (5) validating the tool with prospective users and against previous research. We developed an Excel-based tool that allows working offline, displaying preloaded data, imputing data, and inputting users' data. It calculates annual quantities of milk produced by breastfeeding women for children aged 0–35.9 months, and the quantities lost compared to a defined biologically feasible level. It supports calculations for an individual mother, for countries, and global level. Breastfeeding women globally produce around 35.6 billion liters of milk annually, but 38.2% is currently “lost” due to cultural barriers and structural impediments to breastfeeding. The tool can also attribute a monetary value to the production. In conclusion, the Mothers' Milk Tool shows what is at risk economically if women's important capacity for breastfeeding is not protected, promoted, and supported by effective national policies, programs, and investments. The tool is of value to food and health policymakers, public officials, advocates, researchers, national accountants and statisticians, and individual mother/baby dyads, and will assist consideration of breastfeeding in food balance sheets and economic production statistics. The tool supports the 2015 Call to Action by the Global Breastfeeding Collective by facilitating the tracking of progress on breastfeeding targets. Lack of breastfeeding costs lives, and deprives young children, their mothers, and their countries of important health, human capital, and economic impacts –3.The economic contribution made by women through breastfeeding is still largely invisible in economic data and fiscal decision-making . ApplyinCounting for Nothing, Marilyn Waring discussed  the economic and health system costs of low breastfeeding rates; (2) the costs of breastfeeding protection, promotion, and support programs; and (3) the economic value of breastfeeding and economic costs of ‘lost milk'.Two existing online tools - the Cost of Not Breastfeeding (CNB) Tool, and the World Breastfeeding Costing Initiative (the WBCi Costing Tool) - provide the means to calculate the country-level costs of not breastfeeding , 18, andThe Mothers' Milk Tool has been developed to complement and build on these other tools. The tool makes visible the economic value contributed to society by women's unpaid care work through breastfeeding infants and young children.To develop an online and downloadable tool to estimate the economic value of breastfeeding and the monetary value of “mothers' milk.” We envisage that this evidence-based and user-friendly “mothers' milk” tool will be used by policymakers, advocates, national accountants/statisticians, and researchers to estimate the economic value of breastfeeding and the economic costs of “lost mothers' milk” to support advocacy for breastfeeding-friendly environments. Specific objectives are to (1) describe the development process of the tool, (2) display key features of the tool, and (3) report estimates for selected countries.The design of the Mothers' Milk Tool draws on more than 40 years of research. The development process used 5 steps: define, measure, analyze, design and develop, and verify - DMADV , 22.In the first step, existing tools and scholarly literature estimating the economic value of breastfeeding were reviewed to identify uses, approaches, design features, and data that could be adopted in the development and definition of a suitable product. To identify the key design and methodological issues for such studies, a detailed review was conducted to identify all relevant studies of the macroeconomic value of breastfeeding, and extract summary data on their coverage, data, methods, and results.The review identified that significant but diverse literature exists on the economic value of breastfeeding. The review found around 65 country estimates of the macroeconomic value of breastfeeding, for a total of around 25 countries.The geographic areas covered included Europe, Asia, America, Africa, and Australasia. Several studies produced estimates for groups of countries, and/or for the whole world. Estimates go as far back as 1908, and up to 2018, and for several countries in the 1950s, 1960s, and 1970s. Most identified the quantities and values of milk produced for infant and young child populations aged 0–23.9 months. However, some country estimates were for ages 0–35.9 months. A small number of estimates were of breastmilk supplied for infants only, aged 0–11.9 months or less. The results of the review confirmed not only the relevance but also the feasibility, utility, and sustainability of counting breastmilk as part of national economic statistics. Norway's reporting systems were identified as a model for initial steps toward making the value of mothers' milk visible within a food surveillance framework.This review also considered the potential uses and users of the tool. Most studies aimed to improve the visibility of breastfeeding; motivations included the desire to provide better scientific information for public policy and budgeting decisions; reduce the public invisibility of women's productivity, including breastfeeding; and highlight the need for measures to prevent or address declines in breastfeeding. Some studies were conducted by nutritionists working for international agencies, while others advocated for the government to develop breastfeeding policies and programs. For example, in the early 1970s, World Bank nutrition advisor Alan Berg documented the expanding economic loss associated with formula feeding replacing breastfeeding in countries such as Chile, Kenya, Singapore, and the Philippines over the previous decade, aiming to motivate public action to reverse this decline . LikewisLater studies from the 1990s demonstrated the magnitude of production and the macroeconomic value of mother's milk for countries in Latin America, Sub-Saharan Africa, China, and India –32. StudThe review of studies indicated that measures of actual, potential, and lost milk were the common outputs of interest to users. Also, useful would-be comparisons with national or international targets and benchmarks as well as the capacity to calculate results for significant age categories within the 0–35.9 months age range. For example, some studies examined 12–23.9 months, or 0–5.9 months, while the majority looked at 0–23.9 months including 0–11.9 months.This analysis of the literature also indicated that the tool should have both online and offline versions to cater to diverse uses as well as the intended end use. Potential use includes calculating the production of human milk within food surveillance systems, allowing policymakers to use the results to monitor the results of food security and nutrition policies. Another potential use is the provision of evidence for non-government advocacy, where users from civil society or international agencies could demonstrate the economic significance of breastfeeding and highlight the need for policies targeting breastfeeding protection, promotion, and support.The review also demonstrated that the tool must present key results for selected countries as well as the world, allowing users to see country-level results from a wider comparative perspective. The design also needed to be flexible to meet the main customization needs of policymakers, advocates, researchers, and individuals worldwide, and to allow for future updates and enhancements.In light of the available budget for tool development, a basic version was planned for rapid development and release, to add further enhancements over time based on feedback from users. The type of enhancements being considered is further discussed in the concluding section.Step 2 specified the best open access data available for measurement, and assessed which data allowed future modules to be easily updated. Previous studies used a variety of data sources for key inputs to the calculations, making comparisons difficult. This highlighted the need for the tool to use consistently available open-access data for countries to make the best estimates. It is also important for future modules to be easily or automatically updated with key default data in a timely and efficient manner.There are four key measures. First, the number of infants and young children aged 0–35.9 months is approximated by UNICEF databases . UN popuDue to the different potential uses and users and the limitations of the data, we considered two main stages for the tool development: a basic module and a customizable module.The basic module would include a dashboard that shows the findings and estimations of a selected country or the world using the newest possible preloaded data. This module can also impute missing values of continued breastfeeding to provide a more precise estimate of the value of breastmilk.The tool would also provide for customization, so users can input alternative data such as breastfeeding rates, the size of the population, the market value of human milk, and the currency exchange rate for the country of interest.The tool would allow an individual mother to enter her own breastfeeding experience to calculate the amounts of milk provided for her child.Tool development focused on identifying and pre-loading key data sources and developing a suitable predictive model for breastfeeding rates.It also required the investigation of a suitable basis for estimating milk production levels and exploring sources of evidence on the daily milk intake of breastfeeding children. A further area of investigation was the biologically feasible potential production. The difference between this and actual production levels is the “lost” milk production calculated by the tool.The key data sources and analyses behind the estimates are discussed in Initial investigation of the goals for the tool identified the need for a downloadable tool that can be easily updated with low investment. This stage also identified the need for the user to be provided with key parameters which were fixed in the tool, as well as the potential for the user to make calculations using alternative data sources on breastfeeding or numbers of children born and breastfed.While the main interest was in country-level estimates, sub-national and individual mother calculations were also identified as useful for meeting tool goals.The primary goal identified was advocacy, but additional potential uses included mothers calculating production volume or values over the breastfeeding period as motivation, as well as health professionals supporting and encouraging breastfeeding mothers.Discussions held fortnightly during 2021 by members of the Organization 1 and Organization 2 teams resulted in agreed-upon priorities for the first stage basic version of the tool, and priorities for enhancement in future upgrades.The most important revisions during the development phase were to align the tool with the 0–35.9 age group for infant and young child feeding. Many previous studies were for 0–11.9 months, or at most 0–23.9 months. The tool is unique in its provision of data for the extended age range, which fits into the WHO/UNICEF recommendations for breastfeeding beyond 2 years of age.The development of the tool also considered the maximum biologically feasible levels of breastfeeding. The tool calculates the lost milk on the basis that 98% of mothers can breastfeed, based on contemporary data from Norway  and a reData gaps also influenced tool design. Although DHS surveys include breastfeeding data for 0–35.9 months, the MICS did not. Also, few high-income countries consistently collect data, especially beyond 11.9 months, and some had no recent data. Many did not have data on exclusive breastfeeding. With the substantial data gaps evident during the analysis phase, it became necessary to invest in developing a prediction model for monthly breastfeeding rates for children ages 0–35.9 months. The tool bridges these data gaps to calculate predictions of breastfeeding at each month of age from available national data. This predictor uses a cubic regression model for most countries, though in some countries the best fit was predicted by a linear regression model.per se . This pointed to the importance of deciding on how to attribute a monetary value to breastfeeding to allow this comparison with the conventional official measurement of economic value. Few studies attempted to value the act of breastfeeding per se , 44; whiThe Mothers' Milk Tool places a monetary value of US$100 on human milk produced by breastfeeding women. This is linked to the price of fresh human milk exchanged within the not-for-profit hospital milk bank network in Norway where a US$20 per liter reimbursement of costs is made to donating mothers . Price iThere were two stages of piloting the Mothers' Milk Tool, which occurred during the early weeks of 2022. We aimed for a range of potential user groups to be represented in the two testing groups, coming from a diverse range of countries and global regions. Several improvements were implemented after piloting, mainly to improve presentation and clarity and address functionality issues.A suggestion from reviewers on the first version was to follow a branding guideline. The branding guidelines from Organization 2 were selected and used consistently to design the Mothers' Milk Tool. Based on the comments, additional information was added, such as the introduction, policy brief, and references, to make the tool more comprehensive and standalone.For the country calculator, the Mothers' Milk Tool will provide the country's breastfeeding rates and chart using preloaded data. When the data are not up-to-date or missing, the users have the option to input the missing data using the predictor or enter their own-source data. Using the data, the Mothers' Milk Tool will estimate the annual production, potential production, and lost breastmilk and their values.During development, data from several countries were entered into the tool, and results were compared with results from published studies for the relevant country to assess the validity of tool outputs . This taThe tool was also validated by inviting country IYCF and breastfeeding experts to provide feedback on its functioning, usefulness, plausibility, and reliability of the results and underlying assumptions for that country. A total of 16 potential users responded to the invitation for testing the tool. Respondents were from 12 countries, and their self-described occupations or interest in the tool included advocate, nutritionist, economist, director, peer counselor, nutrition specialist, lactation consultant, medical doctor, and independent consultant. Feedback was centered on the functionality and utility of the tool. User feedback from testing is reported in Estimates were made for a selection of high-, middle- and low-income countries from the global regions, using the prediction model for all those countries where complete breastfeeding data was not available. These countries reflect a diversity of breastfeeding prevalence, some maintaining intact breastfeeding practices at levels consistent with those reported for non-industrial or historical populations, and others with very disrupted breastfeeding practices. Global production was estimated for low- and middle-income countries (LMICs) only due to data limitations for high-income countries (HICs).For a small number of countries, the estimates were tested using historical data series, and for other countries, it was possible to compare the results of the tool with published estimates made at another point in time for the same country. The country selection also reflected large, medium, and small populations, which may approximate the extent to which they are a profitable market for the expansion of commercial milk formula and other baby food sales.After successfully launching the Mothers' Milk Tool offline, we developed the Mothers' Milk Tool online . We are This paper is written because of the researchers' shared beliefs that women's unpaid work including breastfeeding is not well addressed by conventional economic studies which focus on the market economy, to the disadvantage of women and children, and that this reduces the resources invested in programs which are important to the health of women and children in particular breastfeeding. Our focus is on low- and middle-income countries but our study includes global and high-income country perspectives due to our concern to highlight that the latter present a pathway on infant and young child feeding which may harm women's and children's health if followed by LMICs.The authors include one female who is the lead author and three males, and the research team is based in Australia, Vietnam, and London. The three male authors have many years of experience in low- and middle-income countries on programs supporting maternal and child nutrition including in emergencies. The lead author is a former government economist and tax analyst and a qualified breastfeeding counselor in Australia with extensive experience and commitment to supporting women to overcome societal and personal barriers to breastfeeding and to advocate for societal changes to enable them to breastfeed to the extent they see as optimal for their health and wellbeing. The four of us have collaborated since 2020, based on a common interest in improving the measurement of the economic value of breastfeeding and the economic and health system costs of not breastfeeding. In this collaboration, we have sought to develop a robust tool in collaboration with the diverse users, which draws on positivist economic approaches to monetary valuation of non-marketed production yet is also respectful that many women and cultures view it as unnecessary and even devaluing to place a monetary value on breastfeeding. We also respect the loving care that mothers offer their infants and young children regardless of how they decide to feed their children in the circumstance of their individual lives.Global production was around 35.6 billion liters a year. This represents just under half the potential production if women and children 0–35.9 months were universally enabled to breastfeed optimally . ValuingKey results for the selected countries  and the world are presented in Among high-income countries, human milk production ranges from around 11 million liters in Norway, 605 million in the USA, and 51 million in Australia  to 4 million liters in Ireland. In Ireland, around 80% of mothers' milk is lost.Among low-income countries, Nepal maintains human milk production at high levels  with less than 5% lost. Other countries such as Kenya, Nigeria, and Vietnam currently lose around a third or less of production. Likewise, middle-income countries such as Indonesia and The Philippines lost around a third of potential production.The most populous country, India, lost nearly 40%, respectively, with a production of around 8.7 billion liters a year.In monetary terms, the value of human milk production is substantial in most of the selected countries . The monHuman milk produced for infants and young children by breastfeeding mothers is a crucial national food system; this production contributes substantially to national and global food security and health, though much is also “lost”.The economic value of this food production by breastfeeding mothers can and should be measured, to ensure that this important economic contribution is visible, properly valued, well-protected, and sufficiently resourced to continue.A culture of breastfeeding is an important national capital asset with large economic value, which generates a substantial quantity of safe, nutritious, healthy, and environmentally sustainable food for a country's infants and young children. A supportive breastfeeding culture protects the reproductive health of women and minimizes food system pressures on the environment.Where a breastfeeding culture is not visible, valued, and resourced, breastfeeding will diminish, and milk production capacity is lost, due to market pressures from commercial milk formula, hence countries' important 'cultural capital' of women's breastfeeding knowledge, skills, and experience should be protected, and investments made in breastfeeding protection, support and promotion to prevent and restore Lost Milk.The accuracy and capabilities of the Mothers' Milk Tool remain limited by the gaps in available data. The tool does not adjust for exclusive breastfeeding rates during the first 6 months because of data limitations for breastfeeding prevalence and milk intake. Breastfeeding prevalence data is particularly lacking in high-income countries. Up-to-date scientific knowledge is also lacking regarding the biologically feasible potential levels of breastfeeding and the usual human milk intake, particularly among young children.Several enhancements have been identified during development that can be considered for future improvement of the tool. These include modifications to increase its accuracy, flexibility, functionality, and add-on modules to broaden the tool's capabilities.For example, the basic model could be modified to recognize that infant and young child mortality is high in some countries, and the number of births will be higher than the number of breastfeeding children. Especially if better scientific data were available, greater flexibility could also be added to the tool to vary its assumptions about the milk intake of young children who are breastfeeding. Also, breastfeeding has some energy costs for the mother; users could be given the option of adjusting the monetary value of production for the cost of any additional necessary nutrition for mothers.Modifications to allow other approaches to placing a monetary value on human milk can also be considered. Options include allowing the user to enter information on wages for women employed as wetnurses to calculate monetary values per liter of milk or per day of breastfeeding. Similarly, the value of maternal time invested in breastfeeding can also provide an input-based proxy for the monetary value of the milk produced. Estimates of maternal time inputs over the breastfeeding period could be incorporated into the existing tool using available data from time-use studies of breastfeeding and childcare. As commercial trade in human milk expands, using new sources of market data can also be explored for monetary valuation.The individual mother component of the tool could be modified to provide production data for multiple children, and for distinguishing between months of exclusive and partial breastfeeding. Important but more complex programming enhancements that could be added to the tool functionalities for countries include per capita production estimates which would improve its value for cross-country comparisons, as well as flexibility and pre-loaded data to allow time trend analysis. This would also further assist in tracking progress against policy targets.Where countries have policy targets for breastfeeding, the tool could be enhanced to measure the gap between the actual and target level of human milk production. The tool could also provide a page with a prefilled advocacy brief for explaining and presenting country results to policymakers in a suitable format to motivate and guide policy action.Furthermore, by linking the estimates of lost milk production to country data on the volume of milk formula sales or usage, the Mothers' Milk Tool could provide a suitable platform for calculating environmental savings at current breastfeeding rates, and the potential costs  of further declines in breastfeeding.i Costing tool are available to estimate the financing costs of breastfeeding policies and programs  can be found in the article/Written informed consent was obtained from the individual(s) for the publication of any identifiable images or data included in this article.Conception or design of the work and critical revision of the article: JS, AI, TN, and RM. Data collection: JS and AI. Data analysis and interpretation and drafting the article: JS, AI, and TN. All authors have read and agreed to the published version of the manuscript.


Hospitals have a vital role in the future of health systems with upcoming structure, resources, and process changes. Identifying the potential aspects of change helps managers proactively approach them, use the opportunities, and avoid threats. This study presents a mind map of future changes in Iranian hospitals to develop a base for further related studies or prepare evidence for interventions and future-related decisions.This study is a qualitative-exploratory one, conducted in two phases. In the first phase, in-depth and semi-structured interviews were conducted to identify future hospital changes over 15 years. The interviews were analyzed using the content analysis method and MAXQDA 2018 software and holding two expert panels to develop the mind map using the 2016 Visio software.In the first phase, 33 interviews led to 144 change patterns. In the second phase, a mind map of changes was drawn according to experts’ opinions with ten categories: structure and role, knowledge management and research, service delivery, health forces, political and legal, economic, demographic and disease, technological, and values and philosophy, and environmental.Many changes affecting hospitals rooted in the past continue to the future, but the point is the increasing intensity and speed of changes. Healthcare systems need a systematic approach to monitoring the environment to be updated, agile and proactive. These monitoring systems are essential in providing evidence for Macro-level decision-makers. Hospitals are one of the main components of the health system and play an essential role in caring for patients and completing other system functions. They support primary health care providers and the training of health care professionals and researchers. Achieving universal health coverage (UHC) and sustainable development goals requires the commitment of all layers of the health system, including hospitals .Driving forces can challenge hospitals in their strategic and clinical processes while increasing the uncertainty of the future . Trends The mentioned cases are examples of hospital changes regarding the future. This institution’s future has many scopes, dispersion, and changes. It will be vital for managers and decision-makers of the health system to identify and monitor the upcoming changes to manage them proactively. In the past years, Iranian hospitals have undergone many changes, including financial and structural reforms, decentralization, changing payment mechanisms, outsourcing, and increasing the participation of the public and private sectors . Along wThis study tries to identify the future drivers of change that affect hospitals via a systemic approach and map the elements as a mind map. Classifying the drivers into main categories helps analyze the consequences more comprehensively and systematically, and visualizing the data in the form of a mind map enhances visualization of the data and transferring critical messages to the audience.In the present study, Iran hospitals were selected for investigation from the public and private sectors. Iran, with a population of about 85 million people in 2021, is one of the most populous countries in the Middle East region , 19. TheThis study is a qualitative deductive one with an exploratory approach trying to identify the future drivers of hospitals in Iran consisting of two main phases. The first phase was collecting qualitative data and determining the coming changes in hospitals, and the second was mapping the elements as a mind map. The stages and their steps are presented as follows.To collect future changes in hospitals, open and semi-structured interviews were conducted. All the participants were selected using a purposeful and snowball approach in five groups: Ministry of Health and Medical Education (MOHME), health insurance (HI), Health care providers (HP), Hospital Management (HM), and Researchers and members (RFM). Five experts, one per category, were identified to start the snowball method, and interviews continued till saturation. In determining the participants, the main inclusion criterion was to cover the health system sub-systems as much as possible. The following criterion was having more than five years of related work experience or being active in research or education in the health system’s future. The interviews were virtually using Microsoft Team, Sky roam, and phone, and in-person and the interviewer were in the Kerman province of Iran.At the beginning of this phase, in-depth interviews were conducted with the purposeful sampling approach. The main question of the in-depth interview was: What are the main aspects of hospital changes in the next 15 years? The reason for choosing a 15-year time horizon is that numerous studies have worked on determining the future changes in the health system and hospitals; they chose the time range between 12 and 20 years for their research and pointed out that the horizon is suitable for examining future changes . After cA mind map model helps provide efficient, accurate, and creative solutions. This tool can expand thinking in all fields of education, work, and human life  by visuaThe purpose of the second phase was to categorize the ideas and draw a cognitive map of future hospital changes. Two expert panels were held in October 2021, and the second was 11 days apart virtually with the sky room platform. The participants in this phase were selected purposefully among the first phase participants based on the inclusion and exclusion criteria.The first panel presented the changes resulting from phase one to experts. The experts categorized the changes and labeled them by the facilitator’s guide. With permission, note-taking was done during the meeting by two researchers. After finishing the first panel, the research team drew a mental map of the hospital’s future changes using Visio 2016.After mapping the mind map, the second meeting of the expert panel was held. The drawn map was presented during the second session, and the participants were issued potential enhancement or edition points. Finally, the amendments were applied according to the expert’s opinion.To determine the future changes affecting the hospitals, 33 people were interviewed in the first phase 19 were male, and 14 were female, with an average age of 45. By content analyzing the interviews, 144 elements of change were identified, presented in Table In the second phase, 12 experts were selected among the participants of the first phase. Table To prepare the mind map framework, the experts categorized the future changes into ten main categories of: 1) structure and role; 2) knowledge and research management; 3) service delivery; 4) Health forces; 5) political and legal issues; 6) economic; 7) population and disease; 8) technological issues; 9) values and philosophy; and 10) environmental issues. The explanations of each category and its map is mentioned as follows. The whole map consisting all the categories is presented in Fig. hospitals will only focus on patients for whom the other health system providers will not have the necessary facilities and expertise, and patients with complex conditions will be referred to them from other levels, and simpler cases will also be at other levels. To be treated…" (MoH).This code defines the changes that modify the structure of the future hospitals and their roles regarding different stakeholders like society. The related codes are presented in Fig. Providing services will not be limited to hospitals. Hospital teams in the community will actively promote the lifestyle and treatment of patients in their homes…” (HP). "Due to factors such as the growth of technology and information; The quality and safety of services will increase, the preferences of patients will be taken into account in the design of spaces, processes, and services of hospitals…" (HM).Hospitals will have an active, patient-oriented, and user-friendly social role." "Hospital administrators will be aware of the importance of political, social, and economic changes in the hospital environment and will monitor them. I believe future hospitals will establish active environmental monitoring units" (HM).This category examines the evolving roles and position of future hospitals in the realm of knowledge management and research. As knowledge continues to rapidly advance, future hospitals must adapt and restructure accordingly. In order to remain relevant, they will need to transform into knowledge-producing centers that prioritize interprofessional learning. To achieve this, hospitals will need to activate environmental scanning units, which will enable them to stay abreast of new developments and emerging trends. The items related to changes in knowledge and research are shown in Fig. This category shows the changes in providing services in future hospitals. The map of the service delivery section is presented in Fig. Due to megatrends such as globalization or trends of increasing immigration and urbanization, we will see patients and health workers with different cultures from different cities and countries every day…" (RFM). Also, A modification in the characteristics of the health workforce will occur. "With the arrival of the millennial generation, we will see rapid and large changes in employees’ expectations from work environments. The retirement age will increase to compensate for the lack of workforce and skills" (MoH). Health forces codes are presented in Fig This theme refers to the changes that will happen regarding the health workforce in the future and the way that that affects the future of hospitals. The health forces will change in the number and nature of their work processes. There will be an increase in the patient’s and health force’s mobility. "." In my opinion, due to trends such as globalization and international communication, several changes are common between developed and developing countries, such as technologies; the only difference is that usually, these changes in those [developed] countries have either already happened or their speed and intensity are more significant than in developing countries…, another point that comes to my mind is the speed of changes. We constantly change in the workforce. Or we had the expectations of the patients, but the only thing that has happened now is that due to the growth of technologies such as the media and the Internet, their speed has now increased…" (RFM). Another point that can be extracted from interviews is that some changes will facilitate and accelerate other changes. For example, developing health monitoring technologies will enable the development of home care services for patients.The political and legal elements of change are presented in Fig. . "Hospitals will increase partnerships with private sectors and non-governmental organizations to attract more resources…, strategic purchasing will be done more carefully" (HI).The codes of the economic theme are presented in Fig. . "Clearly, due to the increase in life expectancy and the population aging, it can be predicted that the burden of chronic diseases will increase, even in my opinion, the state of multiple diseases and physical and mental diseases will increase together…" (RFM). "Climate changes, drought or global warming and even water and food insecurity that we are witnessing now, can potentially change the patterns of chronic and infectious diseases" (RFM). "The experience of Covid-19 also showed that the threats of emerging and re-emerging infectious diseases can always exist, so future hospitals should not neglect these issues" (MoH).The demographic and diseases-related elements are presented in Fig. . "In my opinion, using cryptocurrencies and technologies such as blockchain will increase hospitals’ financial and information transfers. It would help if you considered that with the growth of big data and the increase in its use, blockchain could be used to maintain this information in the health system" (HI)."In the past years, we consider a significant growth in health technologies, wearable health sensors that help patients control health parameters are one of them. I hope hospital information systems will use this information in the future" (HP). "The development of information analysis methods such as cloud computing can greatly help health systems analyze big data" (RFM).The technological-related elements of the map are presented in Fig. "Associations supporting patients’ rights will become more and more active. Due to the growth of social networks, patients will be able to form a network with each other and express their expectations loudly" (RFM). "The problems of life and the rush and stress that people have now will cause them mental issues; in my opinion, attention to spiritual health will also increase" (HP).The values and philosophy-related elements are presented in Fig. Climate changes, drought and global warming and even food and water insecurity that we are witnessing now have the ability to potentially change the patterns of chronic and infectious diseases" (M 24).Green hospitals will be considered and on the other side the crisis like drought, climate change and pollution will increase the burden of diseases like mental health related ones. More information of the environmental future changes are presented in Fig. The speed of changes in the twenty-first century is faster than in previous years . HealthcIn the future, hospitals will become more specialized and smaller where services will be provided merely by their service providers. Less technical and palliative services will be transferred to primary care providers, nursing centers, or patients’ homes. In the health system profile of Iran, developed by WHO, home-care services are emphasized due to aging and increasing chronic diseases . BesidesFuture hospitals will network with other healthcare providers to share knowledge, experiences, and resources. They will collaborate to identify and respond to community health needs. The network structure allows for economies, proper consumption of resources, development of innovative capabilities of hospitals, reduction of the negative aspect of competition between hospitals, creation of a sustainable market-based health system, and ensuring effective care of patients , 34. TheFuture hospitals will play a more active role in knowledge production by using different research methods and knowledge translation. These hospitals will provide the context of the activities of researchers and facilitate start-ups. Attention to social medicine and educational issues will be strengthened. Health environmental monitoring units will be established to identify and manage existing and future changes and trends. Due to rapid growth and progress in the health system, the field of "health innovation" will be supported, and it examines and monitors health developments and innovations at the global level to increase confidence and reduce risks . The knoPatients with multiple chronic diseases are likely to see about 16 doctors a year. In the meantime, treatments and diagnostic processes may be repeated by doctors, which is dangerous and also costly for patients" [Hospitals will continue their service delivery through multidisciplinary teams and teamwork-based. Patient-centered and providing teamwork services will be necessary to meet the needs of the future . Absolutatients" . One exaatients" . These pIn the future, hospital staff will come from new generations with different characteristics than those in the past. Generation Z, born after 1995, has grown up in the digital age and is accustomed to using technology. As depicted in Fig. One of the critical issues that the health system workforce will face in the future is the need for interdisciplinary competencies and the ability to work in collaborative teams. In recent years, there has been increasing pressure in higher education to train graduates in health systems who can effectively collaborate across disciplines to solve complex problems. An approach to interprofessional education has been developed for this purpose .In addition, there will be an increased emphasis on improving health literacy among hospital staff. High health literacy among healthcare workers is assumed to lead to improved health literacy among patients. There is a positive correlation between health literacy and the health status of the population, and a negative association with health inequalities . TherefoAccording to Rechel , regulatAs presented in Fig. Marketing skills will also be a crucial tool for success in healthcare systems, particularly hospitals, in the future. Service research, design, and strategic marketing are vital components of designing and providing effective healthcare services . ConsequOverall, both insurance coverage and marketing skills play critical roles in shaping the future of healthcare delivery. By investing in these areas, healthcare organizations can improve patient outcomes and stay ahead of the curve in an ever-changing healthcare landscape.The risk of emerging and spreading infectious diseases is rapidly increasing due to global environmental changes and increased migration . The COVIn addition to considering infectious diseases, it is a fact that the world’s population is aging due to declining fertility rates and increased life expectancy . AccordiAntimicrobial resistance poses another challenge for the future of global health. This challenge has the potential to cost billions of dollars annually to the global economy and endanger the lives of ten million people by 2050 . HospitaTechnology development is one of the most emphasized future changes for hospitals and is advancing faster than ever. Digital health is considered one of the main drivers of change in the future of healthcare systems . WearablThanks to new, more effective and personalized medicine, patients are living longer, and many previously incurable diseases are now well-managed as chronic conditions . While tThe concepts, principles, and values of different stakeholders in hospitals have already begun changing and will continue to do so. Patients are no longer passive recipients of services but active participants with increasing expectations for value, satisfaction, and experience . LaurentIn the future, hospitals will increasingly involve patients in treatment processes. One option being considered is changing the name of hospitals from "Hospital" to "Health Homes." Empowering and improving patients’ living conditions will be one of the missions of hospitals, with the aim of improving health outcomes and reducing the workload of hospitals. Ahn also highlights that empowering people with chronic diseases to manage their conditions independently would improve health while lowering costs .The pollution of air, water, and soil has increased significantly in recent years due to industrial reasons and the use of vehicles. If there is no intervention, this trend is predicted to continue. Most notably, low and middle-income countries and rapidly industrializing nations are expected to experience the most significant increase in pollution . Air polClimate change is another challenge that has intensified in recent decades, affecting communities’ health through various means. These include climate change’s effect on the spread of infectious diseases, changes in workforce capacity, and food security . UnfortuMany changes in the healthcare system have been ongoing and will continue to do so, with increasing intensity and speed. This study focused on Iran as a developing country and had a time horizon of 15 years. However, wild card events may occur that could significantly impact the trends mentioned in this study. Future studies should identify these wild cards and evaluate their effects on future changes. The changes described in this study have synergies and interactions that can shape different future scenarios. It is recommended to conduct further research in this regard.Additionally, establishing environmental monitoring units at both the macro level of the health system and within hospitals is suggested to monitor these changes for informed decision-making and planning. The main limitation of this study was the Covid-19 outbreak, which caused difficulties in conducting interviews and holding expert panels. However, the research team utilized virtual communication facilities to overcome these issues.This study categorized future changes in hospitals using a mind map, which has several advantages. We hope that hospital managers and future leaders of the healthcare system will use a forward-thinking approach when planning for the future. As Erwin noted, hospital managers should ask themselves whether their current management approach is optimal .COVID-19 made the research team use virtual interviewing, which made the interviewing process more complex and time-taking. Due to the objection of some interviewees to audio recording, their interviews were recorded in writing, and it restricted access to some participants, Which required many follow-ups.


However, most solutions have not achieved scale or sustainability. Poor usability and failure to address perceived needs are among the principal reasons mHealth systems fail to achieve acceptance and adoption by health care workers. A human-centered design approach to improving mHealth system use requires an exploration of users’ perceptions of mHealth systems, including the environmental, user-related, and technological aspects of a system. At present, there is a dearth of contextually intelligent tools available to mHealth developers that can guide such exploration before full-scale development and deployment.To develop a tool to aid optimization of mHealth solutions in LMICs to facilitate human-centered design and, consequently, successful adoption.We collated findings and themes from key qualitative studies on mHealth deployment in LMICs. We then used the Informatics Stack framework by Lehmann to label, sort, and collate findings and themes into a list of questions that explore the environment, users, artifacts, information governance, and interoperability of mHealth systems deployed in LMICs.We developed the Vinyasa Tool to aid qualitative research about the need and usability of mHealth solutions in LMICs. The tool is a guide for focus group discussions and key informant interviews with community-based health care workers and primary care medical personnel who use or are expected to use proposed mHealth solutions. The tool consists of 71 questions organized in 11 sections that unpack and explore multiple aspects of mHealth systems from the perspectives of their users. These include the wider world and organization in which an mHealth solution is deployed; the roles, functions, workflow, and adoption behavior of a system’s users; the security, privacy, and interoperability afforded by a system; and the artifacts of an information system—the data, information, knowledge, algorithms, and technology that constitute the system. The tool can be deployed in whole or in part, depending on the context of the study.The Vinyasa Tool is the first such comprehensive qualitative research instrument incorporating questions contextualized to the LMIC setting. We expect it to find wide application among mHealth developers, health system administrators, and researchers developing and deploying mHealth tools for use by patients, providers, and administrators. The tool is expected to guide users toward human-centered design with the goal of improving relevance, usability, and, therefore, adoption. In this paper, we present a novel framework for conducting human-centered design evaluations of mobile health  tools used by physician and nonphysician clinical health care workers. We describe the development of our framework, the Vinyasa Tool, aimed at guiding qualitative research on mHealth design and implementation, particularly in low- and middle-income countries (LMICs), grounded in the principles of human-centered design.Governments across the world have implemented mHealth systems that integrate mobile technology into health care delivery to strengthen health systems . These sLimited usability of digital health tools has been identified as a significant uptake barrier among health care workers and other mHealth system users that must be overcome for successful digital health implementation ,10. UsabStudies investigating the use of mHealth solutions have found that factors relevant to technical artifacts, the environment a system is deployed in, and user characteristics have a significant impact on system use. Environmental factors with a bearing on mHealth use include those pertaining to the wider social, political, and economic context in which the solutions are deployed ,19,21-27Given the variety of factors affecting mHealth use in LMICs, human-centered design processes for these systems require comprehensive explorations with end users to examine a priori user interactions with the intervention in the environment in which it will eventually be deployed. Human-centered design methods aim to ascertain users’ desires, needs, and experiences in order to design intuitive systems . Human-cQualitative research methods allow for such explorations and have been used to examine mHealth solutions ,37, studThere is no well-established mechanism for exploring health care workers’ perceptions of and experiences with information systems deployed in LMIC health systems. We therefore developed a tool for guiding FGDs and key informant interviews with end users while optimizing an mHealth solution for a national public health program in India. The Vinyasa Tool is relevant to designers, developers, implementers, and health system administrators seeking to optimize mHealth systems or digitize health information systems, particularly in LMICs. We describe here the development of the Vinyasa Tool through the application of the Informatics Stack framework  to assimWe first describe the key frameworks that have guided inquiry into mHealth solutions in LMIC settings. We searched the literature on electronic health  and mHealth systems in LMICs to identify frameworks developed and used to model these systems or to study their use by health care workers.Chattopadhyay  developeSubsequently, Labrique et al  developeVedanthan et al  categoriMwendwa  used theMaar et al  developeMore recently, Abejirinde et al  developeThe approaches to conceptualizing and depicting mHealth solutions described above successfully capture the environmental, user, and technological factors that affect mHealth solution use. The frameworks described do not explicitly address issues regarding the data, information, and knowledge (DIK) attributes of a system. Per the “Support Tool to Strengthen Health Information Systems: Guidance for Health Information System Assessment and Strategy Development” document from the World Health Organization (WHO), however, DIK is quite central to health information systems design . The impLehmann  developeWe build on the extensive body of work in the frameworks described above and choose the Informatics Stack as a framework we advance to incorporate the DIK attributes, data governance, and environmental factors of a health IT solution. Our tool consists of a list of questions with which to explore end users’ perceptions and experiences of mHealth systems, organized by the levels of the Stack. The tool includes inquiries into the wider contextual issues, user characteristics, human-computer interaction, and technological features that the other frameworks described address. We next describe the Informatics Stack in some detail, followed by our adaptation.The Stack consists of 9 levels at which to view the components, interactions, governance, and interoperability of a health IT solution . Data, iWe used the Stack to abstract the complex structures and interactions of mHealth solutions into simple sections to guide our inquiry with end users. We organized themes and findings from our literature review by the levels of the Stack, compiling a structured list of topics and questions, constituting the Vinyasa Tool.We deviated from the Stack as developed by Lehmann  in 2 sigSecond, we did not include the Stack level “modules” in our tool, as the subsystems conceptualized by Lehmann  do not fUsing the Stack framework with the adaptations described, we assimilated themes and findings from a review of literature to populate the Vinyasa Tool as described below.We conducted a review of the literature on mHealth use by health workers in LMICs to identify findings and themes relevant to health worker perceptions and experiences. The resulting themes and findings were used to form the questions that populated the Vinyasa Tool, as summarized in mHealth, health worker, and frontline worker. We searched the Medline database for articles in English from 2015 to 2020.We reviewed literature on theories of adoption and use of technology  and liteOf these, 2 studies reviewed 82 articles from 2000 to 2018. Agarwal et al  present The listed themes were mapped to Stack levels and sublevels as described in Through an iterative process of clustering and collapsing semantically similar themes, we finalized a list of 71 questions as described in The Vinyasa Tool comprises 71 questions, grouped by the levels of the Stack and arranged as a table as illustrated in The Vinyasa Tool aims to facilitate explorations with research study participants in either FGDs or key informant interviews. The tool covers a broad range of issues relevant to users of mHealth for primary health care, particularly in LMIC settings.We conducted FGDs and contextual interviews with community health workers, mid-level providers, and primary care physicians in Government of Karnataka health facilities in rural areas of Mysore District between August and November 2021. The findings from the FGDs and contextual interviews were triangulated with findings from other human-centered design research methods, including heuristic evaluations, participant observations, workflow mapping, and usability tests. The composite findings from these research activities will be reported elsewhere. We report here our experience with using the Vinyasa Tool as a case study in Our application of the Informatics Stack to develop a tool for qualitative investigation of an mHealth solution in India is a novel contribution to qualitative research to improve mHealth. It enables a comprehensive and flexible exploration of health care workers’ perceptions and experiences of mHealth solutions. Its use would support human-centered design of mHealth solutions for LMICs, resulting in better mHealth use and the strengthening of health systems.It is important to keep in mind that the Stack is a heuristic—a rule of thumb. We have used it as a method for abstracting the complex architectures of health informatics solutions into simpler sections for guiding our inquiries with users. The tool is best used if it is not considered a rigid structural schematic. We expect disagreement over the Stack levels to which we have assigned specific questions or themes because the research findings we used to populate the tool are not necessarily exclusive to individual Stack levels. Rather, some findings overlap across adjacent levels depending on the solution under investigation or the perspective of an investigator. For this reason, we included a column for additional Stack levels for each question to provide flexibility and keep the tool suitable for a variety of solutions and contexts. For example, while addressing work supervision of health workers, questions are in the Organization Stack level of the tool but are also labeled with the Workflow, Behavior, and Adoption Stack level in the additional Stack level column, as illustrated in We developed the Vinyasa Tool for the purpose of studying an existing mHealth solution to aid optimization. The approach we used can be adapted to the development of a digital solution to replace an existing paper-based health information system because the Stack levels are applicable to information systems regardless of the nature of the technology used. We suggest the tool be used in community and primary care settings in LMICs to assess the needs and workflows of physician and nonphysician clinical health workers. We are currently using the tool to optimize the implementation of the Indian government’s noncommunicable disease screening and management tool, targeting 100 million households in India. The Vinyasa Tool can be accessed in IntroductionWe used the Vinyasa Tool to explore the perceptions and experiences of end users of the Comprehensive Primary Health Care Non-Communicable Disease (CPHC NCD) solution in the state of Karnataka, India. The CPHC NCD solution is a national screening and management tool deployed in primary health care systems across India. It supports surveillance and continuity of care for diabetes mellitus, hypertension, oral cancer, breast cancer, and cervical cancer. By 2018, the system had enrolled over 100 million beneficiaries  and is cMethodologyWe conducted 8 focus group discussions (FGDs) with 31 participants in total and 31 contextual interviews with community health workers, mid-level providers, and primary care physicians in Government of Karnataka health facilities in rural areas of Mysore District between August and November 2021. We elicited facilitators, barriers, suggestions, and requests from the participants using the solution. The findings from the FGDs and contextual interviews were triangulated with findings from other human-centered design research methods, including heuristic evaluations, participant observations, workflow mapping, and usability tests. This study was approved by the Institutional Ethics Committee of St. John’s Medical College and Hospital, Bangalore (Ref No 237/2019), and informed consent was obtained from all participants.Our experience using the Vinyasa ToolWe found the tool useful to be a comprehensive but flexible guide for our explorations with users. The tool enabled us to explore a wide range of topics related to the mHealth system being studied. The flow of our discussions jumped spontaneously between multiple diverse but interrelated issues, reflecting the sociotechnical nature of mHealth systems. We were able to keep track of these conversations and guide them using the Vinyasa Tool. The tool also enabled us to organize our observations and findings at the time of data collection to aid recall during subsequent FGDs or interviews for comparison with previous findings.We were able to limit our FGDs to 2 hours (including pile sorting and rating exercises) and contextual interviews to 1.5 hours, keeping within the limits of time acceptable for these sessions . Some toOur tool has some limitations, the chief among which is its length. While we believe it is comprehensive, it requires time and rigor to implement. Developers may benefit from reviewing the tool in its entirety and using components that they want to explore in further depth with their intended users, as they may have already addressed some of the challenges the tool seeks to highlight. Second, the tool was developed in the particular context of primary care settings in India. However, attempts to digitize primary care delivery in most LMIC settings are not dissimilar, and the tool lends itself to easy contextualization in other settings.The Vinyasa Tool facilitates a comprehensive capture of users’ perspectives on mHealth solutions. The tool aids in the understanding of user practices, the evaluation of systems to fix usability issues, and the participation of users in design, all of which are necessary to optimizing health IT solutions . As a toThe dearth of tools to support human-centered design of mHealth solutions and their implementation in LMICs is indicative of the absence of design considerations in LMIC health information system development . While hBy applying the Informatics Stack framework  to key f


Oxytocin has traditionally been known for its physiological effects on muscle contraction associated with birth and lactation, but in the last years is widely used as a biomarker of “positive experiences” in psychology and behavior. Different types of samples have been used for oxytocin measurements with saliva samples having the particular advantage of an easy and non-stressful collection. However, the low concentration of oxytocin in saliva can represent a limitation for its use. For this reason, sensitive assays and even a previous sample treatment in some cases are required for saliva oxytocin quantification. In addition, the lack of standardized and generally agreed-upon approach to peripheral oxytocin measurement leads to large discrepancies between different laboratories, that use different sample treatment protocols and different assays. The main objectives of this review are to describe the current status of the use of saliva for oxytocin measurement, provide details of the different sample processing techniques that can be applied and inform about the analytical techniques and assays available in different animal species, and also in humans for comparative purposes. It is expected that this information can contribute to an increase in the knowledge about the measurements of oxytocin in saliva and to its wider use in the future. Oxytocin is a hormone composed of nine amino acids (CYIQNCPLG) which in many biological samples can have a cyclic chemical structure by the join of disulfide bonds between cysteine residues 1 and 6, resulting in a cyclic core comprising six amino acids with a flexible three-residue amidated tail  Oxytocin is synthesized in the supraoptic and paraventricular nucleus of the hypothalamus. It is tOxytocin has some similarities with arginine-vasopressin, another neuropeptide synthesized in the hypothalamus, which shares with oxytocin seven of nine amino acid sequences, differing only in two amino acids . HoweverTraditionally, oxytocin is known for its physiological effects on muscle contraction associated with labor (uterine contraction) and lactation (milk ejection) . In addiSeveral mechanisms have been postulated to explain the effects of oxytocin, such as the potentiation of neuronal activity in areas of the brain related to cognitive processes, and the reduction of activity in areas that control the autonomic nervous system  as well,There are many studies about peripheral oxytocin measurements that use blood plasma samples , 35, 36.In general, there is little consensus on how to manage the saliva samples, the assays that should be used to measure oxytocin and how to interpret the often-discordant results of various methods . In thisThe main objectives of this review are to report the current status of the use of saliva for oxytocin measurement, describe the options of sample management and processing and provide an update about the analytical techniques described for the measurements of oxytocin in saliva, in different animal species and also in humans for comparative purposes.Although blood plasma is also frequently used to measure peripheral oxytocin concentrations , 35, 36,Saliva has various advantages compared to other sample types that have been used for oxytocin measurements such as cerebrospinal fluid or serumTable In addition, there is in general no high correlation between plasma and saliva concentrations. Quintana et al. concludeMaybe one of the reasons for the divergences found in the relation between oxytocin in cerebrospinal fluid and other sample types, can be the different assays used. As an example, plasma and cerebrospinal oxytocin concentrations were not correlated  when radioimmunoassay (RIA) was used but showed a significant correlation  when an enzyme immunoassay (EIA) was used . Also, tInitially, some authors did not recommend oxytocin measurement in saliva because its concentrations were very low and therefore, difficult to detect with the assays developed at that time . The lowIn animals, dogs and pigs have higher values of oxytocin in saliva than humans, with values usually higher than 200 pg/mL , 67. HowFrom the applicative point of view, changes in salivary oxytocin concentrations have been observed in both humans , 72 and It should be point out the importance of using standardized collection conditions and sampling devices. For example, in dogs, Sarstedt Salivette® yields oxytocin concentrations significantly lower than a SalivaBio Children’s Swab, and citric acid and eating immediately prior to the sample tended to increase oxytocin values .Oxytocin measurements can be made on unprocessed samples or by performing a sample extraction. In addition, reduction/alkylation has been applied for sample processing. Also, a concentration can be done in cases that the limit of the assay detection is higher than the oxytocin levels of the sample to be measured . Table 2The purpose of sample extraction is to obtain a higher purity of the analyte of interest from the sample prior to analysis with the elimination of potentially interfering molecules and the reduction of sample matrix effects . In the 2O), and after a centrifugation the supernatant is applied to the extraction column (equilibrated with acetonitrile and TFA- H2O). The eluate is evaporated, and the samples are reconstituted with assay buffer [There are different methods for sample oxytocin extraction. One of them is solid phase extraction (SPE) that uses different types of columns , 82, 88.y buffer . Alternay buffer . The typThere is controvery in the literature over whether oxytocin extraction is or not necessary. Some authors such as McCollough et al. , Leng anThe lower oxytocin values that are obtained with extracted samples, could be due to the elimination of interfering substances but also due to the loss of the oxytocin of the sample during the procedure .The loss of correlation between analytical values and biological effects that can be produced after the process of extraction .Analytical extraction is expensive and time consuming.However, there are some available commercial kits that recommend the extraction of saliva samples for its measurement, like Arbor assay kit  or CaymaOxytocin in blood can bind to larger proteins, but also there is a fraction which is free. Brandtzaeg et al.  developeLópez-Arjona et al. developeThe performance of a reduction/alkylation procedure would be recommended at the initial stage of the analytical validation of any assay to determine which forms of oxytocin can recognize.Due to the low oxytocin levels in human saliva, it has been described that for some methods, a sample concentration of at least 4-fold is necessary . With thIn veterinary medicine, a previous concentration for the measurement of oxytocin in plasma has been recommended for some methods and species. For example, 10-fold in sheep, goat and pigs, 15-fold in horses and 20-fold in the cow has been recommended for the Enzo Life Sciences kit . HoweverAlthough no reports in saliva have been found, it is described that the storage of samples in a range of temperatures from 0 to 37ºC until 18 h or several freeze/thaw cycles have minimal effects on oxytocin stability in plasma samples . In urinThe oxytocin sequence structure is highly conserved among mammals , so the The main types of assays used for oxytocin measurements in saliva are:Although it was the method that was firstly used for the measurement of oxytocin , 98, it Low sensitivity in some cases that limits the detection of low oxytocin concentrations, existing various reports in which RIAs were not sensitive enough for detecting oxytocin in human plasma , 89, 99,Use of radioactive material and need of special conditions in the laboratory for its performance.In some cases, the low sensitivity can be observed even after extraction and 10-fold concentration of human plasma samples, with 90% of human plasma samples showing values below the limit of detection of the RIA . This haEIA assays have some advantages over available RIA kits, such as a longer shelf life of the reagents, the lack of radioactive materials and a wider detection range. Moreover, EIA requires sample volumes much smaller than those necessary for the RIA, although it depends primarily on whether an extraction is performed prior to assaying. The first EIA suitable for measuring oxytocin in plasma was developed by Prakash et al. , showingIn a study by MacLean et al. (2018), oxytocin concentrations in dog saliva using mass spectrometry (HPLC-MS) and EIA techniques were determined, demonstrating a high correlation  of oxytocin levels in the same samples analyzed with and without extraction. However, the oxytocin concentrations detected by EIA were much higher than those for mass spectrometry. This could be probably because the HPLC-MS detects the specific compound based on a known mass-to-charge ratio. By contrast, EIA may recognize not only the primary form of the target analyte, but also structurally related molecules, including precursor forms and biologically related metabolites .Table HPLC is a technique that separates molecules based on their physical properties. It has been used for oxytocin quantification in saliva of dogs . They foRecently, various researchers have used liquid chromatography coupled to tandem mass spectrometry to assess oxytocin levels in rat, human or mice , 110. AlAlphaLISA technology (PerkinElmer) is an amplified luminescent proximity homogenous assay that uses two bead types, donor and acceptor. The AlphaLISA assay is based on the principle that, when a laser beam is shone on a donor bead, a single oxygen molecule is generated, producing excitation at an adjacent acceptor bead and amplification of a fluorescent signal, which is detected and quantified. Some advantages of this type of immunoassay in comparison with conventional EIA are the small sample volume and requires fewer steps than EIA, with no need for washings. There are few studies that have measured oxytocin with AlphaLISA technology in saliva or other samples. In saliva of pig, canine and bovine species, AlphaLISA methods have shown a good linearity, precision and recovery , 85, 86.Based in the current knowledge, it can be stated that (a) measurements in saliva samples can detect variations in oxytocin concentrations reflecting changes in physiological conditions and, in some cases, correlation between values of salivary oxytocin and cerebrospinal fluid concentrations have been found. (b) In cases of use of assays with a limit of detection not able to quantify oxytocin in saliva, the use of concentration procedures would be recommended, and controversy exists about the need of extraction, although last reports do not support this procedure. (c) There is a wide range of different assays for oxytocin measurements and in any case, it is important to use assays fully validated showing an adequate accuracy and precision to measure oxytocin in saliva in the species planned to be studied. In addition, it would be of interest to know which form of oxytocin  the assay is measuring. Overall, there is a major need of more studies, knowledge, and assay standardization efforts in order to progress in the adequate and proper use of saliva for the measurement of oxytocin and also to determine all its possible applications.


There is much evidence confirming the crucial role played by the gut microbiota in modulating the immune system in the onset of autoimmune diseases. In this article, we focus on the relationship between alterations in the microbiome and the onset of diabetes mellitus type 1 and LADA, in light of the latest evidence. We will then look at both how the role of the gut microbiota appears to be increasingly crucial in the pathogenesis of these disorders and how this aspect may be instrumental in the development of new potential therapeutic strategies that modulate the gut microbiota, such as probiotics, prebiotics, and fecal microbiota transplantation. The gut microbiota is a complex ecosystem consisting of bacteria, fungi, archaea, and viruses living in symbiosis with the human organism. This collection of bacteria, archaea, and eukaryotes that colonize the digestive system has developed this fascinating symbiotic relationship with its host over thousands of years, characterized by a complex mutually beneficial interaction .13 and 1014, a number close to that of all cells in the human body [The total number of these microorganisms is estimated to be between 10man body . MoreoveOnly in recent years, supported by some very important discoveries, and with the fundamental contribution of metagenomics and 16S ribosomal RNA gene sequencing, has the composition and numerous functions of the gut microbiota been better studied and understood .The gut microbiota is physiologically composed of Firmicutes, Bacteroides, Proteobacteria, Actinobacteria, Euryarchaeota, and Verrucomicrobia  Figure .The most represented bacterial phyla are Bacteriodetes and Firmicutes, which make up more than 90 percent of the gut microbiota .The intestinal barrier constitutes a protective defense against pathogens, and toxic and dietary compounds . It is fIn some contexts, this barrier function is lost in what is called Leaky Gut Syndrome, a condition that has been increasingly discussed lately, which some authors say contributes to the onset of major autoimmune diseases such as celiac disease, rheumatoid arthritis, multiple sclerosis, and type 1 diabetes mellitus .The development of the gut microbiota is one of the most interesting and current fields of research. It is certainly affected by environmental influences, the best known of which is the diet .As a confirmation of the symbiotic role between the gut microbiota and the host, early microbiota colonization right after birth deeply influences immunological, metabolic, and allergic diseases .The gut microbiota physiologically plays a symbiotic role with its host, in which it is involved in numerous functions. For example, it plays an immune role in the defense against pathogens. It also plays a key role in nutrition, being involved in the extraction of short-chain fatty acids (SCFAs) and amino acids from foods .Unhealthy diets and obesity are widely known as risk factors for the development of type 2 diabetes . AlteratDysbiosis in the microbiota is associated, with varying degrees of evidence, with a large number of diseases, affecting the gastrointestinal system and others. Those affecting the digestive system include inflammatory bowel disease and irritable bowel syndrome; other disorders include metabolic diseases such as obesity and diabetes, allergic diseases, and neurodevelopmental diseases .Diabetes is a disease of the endocrine system characterized by high blood glucose levels, which can be recognized by several underlying conditions. The predominant form appears to be type 2 diabetes, which accounts for 90–95% of cases .Diabetes is one of the most prevalent diseases globally: in 2014, 9.3 percent of Americans were reported to have diabetes (29.1 million people) .The incidence of this disease is steadily increasing, and it is estimated to affect 693 million adults globally by 2045, a 50 percent increase from 2017 .The main cause of morbidity and mortality of this disease is due to its micro- and macrovascular complications, such as cardiovascular disease, nephropathy, retinopathy, and diabetes-related neuropathy .Type 1 diabetes mellitus (T1DM), is mainly characterized by insulin deficiency, while type 2 diabetes mellitus (T2DM) is characterized by insulin resistance with relative insulin deficiency. Type 1 diabetes mellitus, also known as juvenile diabetes, remains the most common form of diabetes in childhood, although the rate of type 2 diabetes mellitus is steadily increasing .In most patients with type 1 diabetes mellitus, destruction of pancreatic beta cells that secrete insulin occurs through an autoimmune mechanism. This mechanism, mediated by autoantibodies, is sometimes referred to as type 1A diabetes .In clinical practice, the assay of autoantibodies against GAD65 (glutamic acid decarboxylase 65), IA2 (40 K fragment of tyrosine phosphatase), insulin, and ZnT8 (zinc transporter 8) is indicated .Type 1B diabetes refers to a minority of patients who, although they have the clinical features of type 1 diabetes mellitus, have no detectable autoantibodies, no evidence of autoimmune beta-cell destruction, and in whom no other causes have been identified. Another characteristic feature of type 1 diabetes mellitus is inappropriately low levels of insulin and C-peptide relative to plasma glucose concentrations, while high levels of fasting insulin and C-peptide point toward a diagnosis of type 2 diabetes mellitus .In the pathogenesis of type 1 diabetes mellitus, many researchers have speculated that a key role may be played by viruses according to several mechanisms. According to some, viruses act by destroying beta cells, while for others they activate an autoimmune-type response directed against these insulin-secreting cells .The viruses most often called into question are enteroviruses (such as Coxsackie B1 and B4), CMV, rubella, and mumps .There is a minority of patients who develop type 1 diabetes mellitus in adulthood, often initially diagnosed as type 2 diabetes mellitus. These patients of older age may have circulating autoantibodies directed against pancreatic beta-cell antigens (ICA or GAD65) .Latent autoimmune diabetes in adults (LADA) is diagnosed in these patients. From the European multicenter study “Action LADA,” it was found that nearly 10 percent of patients with diabetes mellitus arising in adulthood had autoantibodies directed against pancreatic islets . These aResearchers have long hypothesized that patients with type 1 diabetes mellitus might have a different composition of the gut microbiota than that of healthy people .This hypothesis is related to the finding of an increased incidence of type 1 diabetes mellitus diagnoses in developed countries, so it was thought that environmental factors might be involved in the pathogenesis .The hygiene hypothesis, which correlates improved hygiene conditions with increased incidences of autoimmune diseases, has been known for some time.In experiments conducted on laboratory mice, an increased incidence of diabetes was found in those raised in a germ-free environment .It is known that there is a profound link between gut microbiota and the immune system, the dysregulation of which underlies many important diseases.Dysbiosis is hypothesized to be the cause of dysregulation of the development of the inflammatory response underlying the onset of inflammatory bowel disease .Dysregulation of the immune system is also implicated in the onset of other major autoimmune-type diseases, such as rheumatoid arthritis, psoriasis, multiple sclerosis, and type 1 diabetes mellitus .This evidence is supported by another paper from 2018  that staBifidobacterium infantis, which plays a critically important role in breast milk metabolism, due to several reasons such as an increase in cesarean deliveries.To explain this phenomenon, the authors hypothesize that underlying it is a decrease in the presence of certain microorganisms, such as This observation is reinforced by another important study conducted in Denmark , in whicSome important findings help us to better understand the link between type 1 diabetes mellitus and the gut microbiota.Bacteroidetes was found, while in healthy subjects, that of Firmicutes was found to be increased [In autoantibody-positive patients, an increase in the proportion of bacteria belonging to the phylum ncreased .This interesting article summarizes the main evidence regarding the different compositions of the gut microbiota between patients with type 1 diabetes mellitus and healthy patients  Figure .Furthermore, in patients with type 1 diabetes mellitus, a decrease in the microbiota producing SCFAs (short-chain fatty acids) has been found , and forAkkermansia muciniphila, a strain that produces SCFAs [This hypothesis is also supported by the finding in murine experiments in which fecal microbiota transplantation (FMT) decreased the incidence of type 1 diabetes mellitus only in those transplanted with selected feces with an abundance of es SCFAs .We have previously mentioned the link between endotoxemia and the development of metabolic type diseases such as type 2 diabetes mellitus. Gut epithelial and endothelial cell–cell junctions are composed of transmembrane proteins called tight junctions (TJs) . InflammThis evidence comes as a result of Cani’s seminal work in 2007 in which he highlighted how poor nutrition increased metabolic endotoxemia with harmful consequences for the body . This fuThere is a complex interplay linking diabetes pathogenesis, and the microbiota and their metabolic products. With regards to these products, short-chain fatty acids (SCFAs) play a pivotal role. Short-chain fatty acids, including butyrate, are products of fermentation of food residues. Butyrate appears to play a key role in metabolism, modulating satiety, blood sugar, and cholesterolemia .The report that short-chain fatty acids play a protective role against diet-induced obesity and insulin resistance has been described in the literature .In addition, oral administration of sodium butyrate in mice significantly increased plasma insulin .According to some theories, diabetes mellitus type 1 may develop due to an alteration of the intestinal epithelial barrier, in the modulation of which short-chain fatty acids play a key role. In experiments in non-obese diabetic mouse models, there was an enhancement of beta cells in those that received butyrate and acetate ,52.In light of this evidence, the possible role of prebiotics and fecal microbiota transplantation in preventing diabetes complications has been suggested ,54.The microbiota may also, through the production of short-chain fatty acids, have an impact on diabetes complications such as atherosclerosis and peripheral artery disease, as SCFAs are believed to reduce inflammation and thus have a negative effect on the formation of atherosclerosis .Some very other interesting piece of evidence comes from the TEDDY . The TEDDY study, among its many areas of research, was also interested in the relationship between the onset of juvenile diabetes and the gut microbiota. This study revealed the protective role of short-chain fatty acids against diabetes mellitus type 1 .Type 1 diabetes mellitus falls among the autoimmune diseases, and similar to other autoimmune disorders, there is a close association with genetic factors.Many researchers have wondered whether there might be a link between HLA (human leukocyte antigen) genotypes and the development of the gut microbiota.A landmark study, conducted in Sweden over two years, involved infants whose fecal samples were collected at one year of age, the time when the autoimmunity that characterizes type 1 diabetes mellitus typically develops.Fecal composition was correlated with HLA genotype, and it was found that genotype may have an association with the gut microbiota of infants, resulting in the first study in which HLA genotypes were found to correlate with changes in the gut microbiota in human patients .Probiotics are defined as microorganisms that are beneficial to the body, while prebiotics are non-digestible foods that stimulate the growth of certain bacterial groups in the intestinal tract . AttemptSome important evidence on the use of probiotics comes from a recent study conducted in India, in which probiotic-treated children saw improved glycemic control indicated by a reduction in HbA1c and insulin treatment requirement .This represents an important starting point, although there is still a long way to go in this regard, and many studies are still needed.With the use of fecal microbiota transplantation (FMT), as opposed to probiotics, one goes about manipulating the composition of the gut microbiota in a significantly more invasive way.A randomized controlled trial conducted in 2020 by de Groot et al.  demonstrSome other important evidence comes to us from a recent study in which two patients with type 1 diabetes mellitus underwent fecal microbiota transplantation .The results were surprising; one of the two no longer required hypoglycemic treatment during the months of follow-up in the study, while the other discontinued insulin treatment, and only took oral hypoglycemic drugs. These patients underwent multiple sessions of fecal microbiota transplantation, indicating a kind of “reinforcing effect.”On the strength of this evidence and the multiple insights gained over time, fecal microbiota transplantation is being studied as a therapeutic strategy for diabetes mellitus as well. Just to tie in with our statements, we cite the very recent case of a 24-year-old young man with type 1 diabetes mellitus and malnutrition successfully treated with fecal microbiota transplantation .All of this evidence gives hope that better glycemic control can be achieved in the future through these new therapeutic strategies.It is interesting to see how quickly certain aspects in medicine change when dealing with a topic as interesting and rich in news as the gut microbiota. In a recent article, the established relationship between alterations in the gut microbiota and the onset of type 1 diabetes mellitus was reiterated, while a clear relationship between the microbiome and the pathogenesis of LADA has not yet been shown .All this changed within a few months. The link between autoimmunity and the microbiota has also been explored in the context of latent autoimmune diabetes in adults (LADA).A study was conducted in 2021 in four groups of people, one with patients with type 1 diabetes mellitus, a second with type 2 diabetes mellitus, another with LADA, and a control group with healthy patients, who were dosed with serum and fecal metabolites .Faecalibacterium spp., Roseburia spp., and Blautia spp.It was found that in the microbiota of LADA patients, there is a decrease in These are short-chain fatty acid-producing bacteria which, as already discussed in this paper, seem to be involved in diabetes pathogenesis. In conclusion, LADA patients have a change in gut microbiota which closely resembles that of type 1 diabetes mellitus patients and has significant variations compared to the microbiota of healthy people. The role of immunity resulting from the proper development and functioning of the gut microbiota and the onset of LADA has therefore been examined again in some recent work , and theFinally, with the intention of emphasizing once again how important this promising new line of research is, we cannot fail to mention this very important trial being conducted in China  in whichAs we have seen, step by step, we are getting closer to a better comprehension of the influence that the gut microbiota has on many physiological and pathological processes and its relationship with autoimmune diseases. It is now clear how the gut microbiota is a fundamental constituent of the human organism. This superorganism, whose development is affected by countless factors, is increasingly implicated in the pathogenesis of various diseases .The gut microbiota begins to develop from the earliest months of life, as does our immune system, so the hypothesis of an existing interplay between the two of them is fairly reasonable .We have seen how diabetes mellitus continues to be one of the big issues in public health, both because of its high prevalence and important impact on morbidity and mortality. In recent years, thanks to important insights from researchers and the parallel advancement of technology (just think of the introduction and spread of gene sequencing), we have been increasingly able to delve into the relationship that links these two major chapters of modern medicine.Interest in the relationship between type 1 diabetes and gut microbiota has grown tremendously in recent years .We are confident that in the coming years there will be decisive steps forward in understanding the role that the microbiome plays in the pathogenesis of this important disease. The pathogenesis of diabetes mellitus is a multifactorial etiology, in which genetic and environmental mechanisms all have their influence. Therefore, when conducting research and attempting to recreate the right environmental substrate, such as by modifying the gut microbiota, if genetic predisposing factors are not also taken into account, many of the results will be inconclusive. This is the real challenge of modern medicine, with an increasingly personalized approach to the individual. Additionally, this is precisely why it is very difficult to conduct research that manages to take into account all the variables involved in the onset and progression of this disease.Speaking of the gut microbiota, the latest research is focusing on the role of some of its less numerous but no less important components, namely viruses and fungi. One of the latest frontiers is the mycobiome, which includes fungi and yeasts, and its potential connection with type 1 diabetes mellitus . Viroma In this case, however, the connection between these two topics seems to be less distant, having already found a link between viral infections at a young age and the onset of type 1 diabetes mellitus, although more studies are clearly needed on this issue. Deepening the understanding of the gut microbiota will allow new therapeutic approaches to be attempted with the aim of improving patient management of the disease.Diabetes mellitus includes fearsome microvascular and macrovascular complications .As we shall see, one of the therapeutic goals to be achieved by modulation of the gut microbiota is precisely that of better glycemic control, thereby reducing glucotoxicity and the incidence of the various complications that accompany this terrible disease. A relationship has been shown between alterations in the microbiota both in the classic form of diabetes mellitus, type 1, also known as juvenile diabetes, and in LADA, whose defining characteristic is precisely that it arises in adulthood. This speaks volumes about how complex the world underlying immune activation is in these diseases. In both cases, we have underlying insulin deficiency, that is rapid and dramatic in type 1 diabetes mellitus, or late and slower-progressing in LADA. One of the new challenges in medicine would be precisely to understand why such different expressions of insulin deficiency occur in these two disorders that have similar pathogenetic mechanisms. For now, we have mostly pre-clinical evidence and case reports, but considering the solid rationale, we believe future studies will advance our knowledge. There are multiple strategies with which to interact with the gut microbiota for therapeutic purposes, e.g., the use of probiotics and prebiotics, and fecal microbiota transplantation (FMT), which is certainly the most invasive and but also the one with most potential. Many researchers have taken an interest in the use of prebiotics and probiotics as a supportive strategy for the management of type 1 diabetes mellitus , with enThe use of fecal microbiota transplantation has now become a viable therapeutic option for clostridium difficile infection (CDI), a dreaded condition that is, at its root, a dysbiosis of the gut microbiota ,74.In this regard, a new and interesting systematic review conducted on this topic (FMT and T1DM)  also citWe are still scratching the surface of the underworld which links our immune system and our microbiota. Every day there are new discoveries in the vast world surrounding the gut microbiota, and this is particularly evident in its relationship to the onset of type 1 diabetes mellitus and latent autoimmune diabetes in adults (LADA) as they are related to a dysfunction in the immune system.Our immune system is profoundly influenced by external factors, and the importance of the microbiome as one such factor is being increasingly recognized. These aspects are particularly fascinating for several reasons.First, it could help identify those at risk of developing diabetes at an early age and create a screening program.Then, clearly, it could suggest an integrated approach to treatment. Interventions on the microbiome could alter the course and natural history of diabetes in young patients, delaying insulin therapy and helping preserve pancreatic beta cells.If risk factors for the occurrence of these diseases could be identified, interventions could be taken to prevent their occurrence. In addition, we have seen how recent findings on the link between the gut microbiota and these diseases are being exploited to develop new therapeutic strategies, such as the use of prebiotics and fecal microbiota transplantation.The era of precision medicine is approaching, and the microbiome appears to be destined to play a key role.