Based on the transparency theory, this study investigates the appropriate amount of transparency information expressed by the in-vehicle robot under two channels of voice and visual in a proactive interaction scenario. The experiments are to test and evaluate different transparency levels and combinations of information in different channels of the in-vehicle robot, based on a driving simulator to collect subjective and objective data, which focuses on users’ safety, usability, trust, and emotion dimensions under driving conditions. The results show that appropriate transparency expression is able to improve drivers’ driving control and subjective evaluation and that drivers need a different amount of transparency information in different types of tasks. With the rapid development of intelligent vehicles, drivers’ requirements of more intelligent assistances from the cockpit have increased. More vehicles are equipped with virtual image voice assistants or vehicle robots with a physical entity, etc. These in-vehicle intelligent assistants enhance the intelligence level of the cockpit and can execute diverse tasks. The interaction between human and in-vehicle robots is considered as an integration of a complex social and technical system , which nAnthropomorphism and proactivity have been widely studied for the future in-vehicle robots. A study by Waytz et al.  showed tAn important condition for a robot to be able to interact fluently with humans is that the two can share a common cognitive framework  and formThe expressed in-vehicle robot’s information to drivers needs to be selective.The appropriate amount of transparency information for different driving situations needs to be determined.Using cognitive theory to design in-vehicle robots to provide appropriate expression to humans has not been widely studied. This paper applies situation awareness-based agent transparency theory to design in-vehicle robots. The objective of this paper is to explore the appropriate amount of transparency information that can assist human decision making by conducting experiments. Because the inappropriate amount of information while driving, especially in critical situations can affect safety, usability, workload, and trust, the following hypotheses are made.In order to test these hypotheses, in-vehicle robot transparency design has been made at three levels of perception, comprehension and projection based on SAT theory, including channels of voice and visual in the design. Then, experimental evaluation of the transparency design hypothesis has been carried out in selected driving scenarios. After analyzing the experimental results, conclusions of transparency design of in-vehicle robot proactive interaction in different scenarios have been made.The contribution of this paper is that it gives results on how an appropriate level of transparency expression affects drivers’ driving control and subjective measurement. It also identifies that drivers need a different amount of transparency information in different types of scenarios. Results can provide guidance to help design in-vehicle robot interface with appropriate transparency.As human–robot interaction (HRI) becomes more complex, many guidelines and design criteria have been developed depending on the specific applied scenarios . A shareAs intelligent systems become complex, researchers have begun to focus on proactivity. There is some consensus in the research field regarding the definition of proactivity, mostly in terms of the role and state of the initiator of the interaction. Keith et al.  argued tMultimodal interaction is also widely used in proactive interaction scenarios. For an anthropomorphic robot, dual-channel interaction between speech and vision is crucial  and can The core of contemporary research on proactive interaction focuses on the technology domain. Most of them are based on the decision making of artificial intelligence models to enhance situation awareness, consciousness perception, and emotion perception. Specifically, in the in-vehicle scenario, proactive interaction can help users collect and process information in the environment, therefore reducing the user’s information processing burden. A further study  proposedProactive interaction is of high importance due to the development of intelligent interface. However, the current work on proactive interaction is focused on the related HRI system in the technical field , which iUnderstanding the reasoning process behind the output of an intelligent system in a dynamic environment is of great importance . Van DonIn the context of automation, an understanding of the behavior of technical agents is important to ensure good interactions between human and technical agents. This understanding is often referred to as “transparency”. Lyons  argues tIn terms of information content, clearer and more accurate information delivery can enhance human trust . It has Endsley’s situation awareness (SA) theory  proposesThe SAT model also consists of three levels. At the SAT Level 1, the perception level, the operator should be provided with the agent’s goals and its perception of the environmental situation. At the SAT level 2, the comprehension level, the operator should be provided with the agent’s understanding of the situation and the reasoning process of the action. At the SAT level 3, the projection level, the operator should be provided with the agent’s projection of the future outcome. All three levels of the SAT model describe the information that the agent needs to convey to maintain transparent interactions with humans. The operator is, therefore, able to understand the agent’s intentions, reasoning process, and predicted outcomes, which leads to better information sharing and a common mental model of their communication. The presence or absence of each level of information in the SAT determines whether the user is able to understand the perception, comprehension and projection of the current information expressed by robots. The design needs to consider that each level of information can be combined to obtain an appropriate transparency that promotes mutual human–robot understanding without increasing the workload. Conducting phase analysis through an SAT model is a way to contribute to transparency between humans and robots. The usability of the intelligent system, the emotional experience of humans, and the level of trust can be measured. Related studies have also applied the SAT model for interface design to conduct explorations, including robot action interfaces and UxV action interfaces ,32.According to the theory of situation awareness, the human cognitive process includes three levels: perception, comprehension, and projection . In the In the design of in-vehicle human–robot interaction, it is necessary to consider the appropriateness of the amount of information in different channels and different SAT levels. The impact on several aspects needs to be examined such as driving safety, usability, and emotion. The research framework is shown in In order to promote appropriate transparency, Lyons argues that an opportunity to foster transparency between the human and the robot is from the human–robot interface. The human–robot interface includes three levels: informational, communicative, and physical . Each leFor specific designs, interface features at the informational level need to be considered to avoid too much information or non-intuitive displays, which may confuse and frustrate the user of the robotic system. Interface features at the communication level need to be considered to avoid the robot’s inappropriate responses, which affects user trust and performance. Interface features at the physical level may include the robot’s emotional expression, effectively describing the robot’s emotional state.In transparency design assumptions, the amount of information and information intuitiveness should be considered at the informational level. At the communication level, communication smoothness and response timeliness should be considered. At the physical level, emotional expressions should be considered.Human–robot transparency design requires identifying certain interaction timing. The identification enables the design of in-vehicle robots to present the driver with the appropriate level of transparency to facilitate the driver’s understanding. The in-vehicle robots give appropriate information that conforms with driver’s cognition, thus resulting in transparency of the entire interaction process. We have explored the possible design combination and excluded the designs that were clearly unreasonable for each interaction timing in a given scenario. For example, considering communication smoothness and response timeliness, the information can be neither too much or too little. Then, the design pattern for each transparency level emerged, forming the transparency design assumption.Transparency was first analyzed from the perspective of information intuitiveness. From design exploration we conducted before the experiment, we found that when users were given information at the comprehension and perception levels, they can accurately identify the existence of the projection level. However, when the information at the projection level existed alone, users defaulted to the existence of perception and comprehension levels of information. It showed that subjects were unable to cognitively recognize low-level transparency information in the presence of high-level transparency information. When analyzed at the physical level, emotional expression providing information at the perception and comprehension levels may affect subjects’ emotions. Therefore, perception and comprehension levels of information should still be taken into account in the transparency design assumptions.In the proactive interaction condition of the in-vehicle robot, it has more information that needs to be shared with people, and therefore, it requires a higher transparency of expression. At the perception level, considering emotional expression from the physical level, voice cues can increase the robot’s anthropomorphism and enhance human emotions in the corresponding scenarios. At the comprehension level, considering the informational level aspect, the robot needs to covey the information it perceived to people, and how it comprehends the information needs to be transparent in the voice channel. At the perception and comprehension levels, information in the visual channel, the information intuitiveness, and task fluency are considered, and the comprehension level information is chosen to be retained. At the projection level, considering information intuitiveness, the voice channel gives easier understanding compared to the visual channel, so that the projection information is designed to be expressed through the voice channel. Therefore, the design of the projection level is assumed to include the voice channel information. It is expected that the visual channel projection level information can play an auxiliary role to the voice channel information to strengthen the robot’s expressiveness. Incorporating the communication smoothness into the comprehensive consideration, the presence or absence of visual channel SAT3 level information can be examined. The design assumptions are listed in To summarize the above research approach, the transparency design assumes that the human–robot communication can be more understood by each other and interaction can be more efficient. What kind of design pattern can reach the above goal needs to be determined. Our research approach is first to use the SAT model to analyze the stages, splitting the entire human–robot interaction process into three stages. After the stages were analyzed, we adopt the human–robot interface levels of informational, communicative, and physical guidance. We then further expand human–robot interface levels into the amount of information, information intuitiveness, communication smoothness, response timeliness, and emotional expression for each stage to analyze the information under voice and visual channels and SAT levels.Thirty subjects , with the age ranging from 22 to 40 years  with post hoc pairwise comparison was conducted in the speeding task. A summary of the experimental results in separate tasks can be seen in the following sections.As shown in As shown in As shown in As shown in As shown in As shown in As shown in The results of the behavior data showed that the subjects in experimental group 1 were significantly higher than those in experimental group 2 and experimental group 3 in terms of saccades time and fixation time.As shown in As shown in In the telephone task, the design with SAT1 perception level, the voice channel information (hereafter referred to as the ringing group) in group 2 enabled subjects to obtain more positive emotions and reduced the workload of the subjects. This was probably because the added information enhanced the anthropomorphism of the robot. However, subjects had significantly worse horizontal control of the vehicle, and the saccades time and fixation time increased significantly. This suggests that the subjects were overly distracted by the robot and had reduced concentration on the driving task, which may cause danger. As for the subjective data, subjects rated the usability of the ringing group lower, and significant differences were found mainly in the aspect of time required to complete tasks. It can be obtained that task disfluency due to lengthy speech triggered subjects’ lower usability ratings of the robot. In addition, the increased information at the expense of time spent did not improve usability ratings in terms of ease of task completion and satisfaction of support information. Overall, the existence of SAT1 perception level provide higher transparency. However, it does not suggest better cooperation between human and robot.In the speeding task, the design with SAT2 comprehension level presenting voice and visual channel information as well as SAT3 projection level showing voice channel information had better information transparency. In terms of safety, group 1 had the best data performance in terms of vehicle horizontal control. Adding the SAT3 projection level visual channel information or SAT1 level voice channel information would make the driver’s horizontal control of the vehicle worse. From the subjective data, having SAT3 level visual channel information resulted in significantly higher workload and lower arousal and dominance. The speed limit expression at the projection level caused subjects’ greater workload and did not help in driving, indicating that it was an unnecessary distraction for the driver. The presence or absence of SAT1 level with voice channel information (‘oops’) did not significantly affect workload. Therefore, in the speeding task, the design of the in-vehicle robot can omit the SAT1 stage information, which is not very helpful for the task, and the complicated SAT3 level visual information can be similarly excluded to increase safety and reduce the workload.In summary, we analyzed the appropriate amount of transparency information for in-vehicle robots in a proactive interaction scenario. The experimental groups with SAT1 performed poorly in both scenarios. In order to improve the effectiveness of message delivery and help drivers concentrate, designers should carefully consider increasing voice channel information at the SAT1 perception level. The design that performs better in telephone tasks has SAT2 comprehension and SAT3 projection levels of both voice and visual channel information, which is different from the better design for speeding tasks. In the speeding task, the SAT3 projection level and visual information make the workload of subjects significantly higher, and the driving safety is compromised. Analyzing the task characteristics, we can conclude that the telephone task belongs to function, while the speeding task belongs to critical scenarios. The driver’s concentration level on driving tasks in the two scenarios is different; therefore, the driver needs different robot transparency.The advantage of higher transparency for the in-vehicle robot is that it can help drivers judge the situation, reduce drivers’ need to reprocess the information provided by the robot, and increase the drivers’ decision-making confidence. However, higher transparency also has its own disadvantage. In the case of insufficient attention and mental resources, too much information is not only not fully received by the human but also affects the driver’s driving performance, especially when implicit information such as robot expressions that require extra mental resources from the driver appears. These results suggest that the ‘highly transparent’ assumption made by previous work needs careful consideration. In critical scenarios, it is recommended to design more direct voice information without adding extra workload. In non-critical driving scenarios, designers can consider giving robots a more transparent response to drivers while maintaining task fluency.The experiments were based on transparency design assumptions, and they yielded preliminary results for the exploration of suitable transparency. We are able to draw enlightening conclusions from different measurements, and the purposes of the experiments are essentially achieved. However, due to the experimental limitations, it was not possible to exhaust the possible design assumptions, and there may be more appropriate transparency designs for specific scenarios.The relationship between saccades time and driving safety was also noted in both scenarios. In the non-critical scenario, an increase in saccades time and fixation time on the robot undermines driving safety. In the critical scenario, on the contrary, an increase in saccades time and fixation time of the robot improves driving control. The reason for this result derives from the difference in the type of tasks that the driver and the in-vehicle robot achieve together in the two scenarios. Taking workload into comprehensive analysis, in the case of joint driving tasks such as the speeding task, the robot’s information alerts can share the workload for the driver and obtain better driving performance. However, when the robot is completing non-driving tasks such as picking up the phone, the increase in saccades time and fixation time indicates that the driver is more involved in non-driving tasks and does not concentrate on driving tasks, so the driver tends to have poor control of the vehicle. Further analysis revealed a tendency for the reduced self-reported workload when drivers were more involved in non-driving tasks. This may be due to the higher workload of the driving task compared to the non-driving task, which is also able to corroborate with the multi-resource prediction of dual-task interference in the multi-resource theory (MRT) proposed by Wickens .In this paper, we migrate SAT theory into an in-vehicle robot design method and conduct a proactive interaction design of in-vehicle robots based on transparency design assumptions. The results of the experiment show that the driver’s driving control, behavior, and self-reporting results produce differences under different in-vehicle robot transparency. Overall, anthropomorphic information of perception level, though bringing a better emotional experience to the driver, can cause poorer driving performance. In the critical scenario, because of the need to ensure timely and effective information, the driver can accept lower information transparency of the in-vehicle robot than in the non-critical scenario, retaining only key information. The conclusions can be distilled into design guidance: in the in-vehicle scenario, information transparency design assumptions can be made for both voice and visual channels based on SAT theory to help designers arrive at interaction solutions with more appropriate transparency. The guidance can also give a methodology to solve the transparency challenge that lies in future research of human-centered shared control . FollowiAt this stage, the multi-channel interaction design is not separated from transparency. The multi-channel content is only used as an independent variable of transparency change to serve the transparency design. In terms of future work, we will go further to establish the design model integrating multimodal and transparency, concerning input and output modalities , and the


Most of the sub-Saharan African countries including Ethiopia were affected by the food insecurity issue. This study aimed to analyze the drivers of food insecurity, the choice of livelihood strategies, and factors that impact the choices of food security strategies in response to food insecurity in Abay Chomen District of Ethiopia's Oromia region, Ethiopia. The result of this study is based on primary data and obtained from 150 randomly chosen sample households and secondary data generated from various sources. As for the technique of data analysis, this study employed descriptive statistics for the food insecurity index, as well as a binary logistic model and a multinomial logit model for the choice of household livelihood techniques. The findings of the survey showed that 51.3% of the households were found to be food-insecure and 48.7% food-safe in the study area. Furthermore, the result indicated that the average calorie consumption of the households surveyed was 2008.54 kcal for each adult equivalent per day, which is below the lowest calorie necessity of 2200 kcal. The estimated logistic model outcome on the drivers of household food insecurity confirmed the oldness of the household leader, larger family holder, and off-farm income affects negatively, while the gender of the household leader, the size of the built-up area, the number of livestock holdings (except oxen), the number of oxen owned, access to credit, the participation in the sale of cattle, and others affect positively. In addition, the multinomial logit model result indicates that the educational status of the household leader, the size of livestock farming, the number of oxen possessed, access to credit, remoteness to the market, and monthly agricultural earning are the main drivers of the choice of livelihood strategies of concern for the food insecurity of households. As a result, this research attempted to produce a result of analysis with a defined scope, although many questions remain unsolved. Future studies should concentrate on presenting fundamental data on the factors that affect food security status and livelihood strategy, the social, political, natural, and environmental aspects, the descriptive information on the shopping habits of people who experience food insecurity, and the key aspects that increase the vulnerability of the rural poor to food insecurity. It is predicted that around 870 million people worldwide were undernourished (in terms of food energy) between 2010 and 2012. After the 2016 rainy season failed, the government estimated in early 2017 that 5.6 million people lived from February to June . As a poThe central economic sector that is consistently negatively impacted by climate change is agriculture . All parThe concept of food security has changed greatly over time, with many researchers, scholars, and organizations refining and broadening its definitions. The word “food security” is dynamic and has expanded over time to embrace new dimensions and levels of examination . With a Tactics for making a living are actions taken by households to support their way of life. It varies on both the micro- and macro-scales. The various approaches to describing household livelihood strategies that are available in the real world have been reviewed. Rural families create a diverse range of activities and social support abilities known as “livelihood diversification” in their struggle for survival and development in their standards of living and ways of generating a living. The problem of food insecurity, according to Ref. , can be A study conducted by  found thAccording to a study  on farmeAs shown in a study conducted by  on the dP=0.01) in the farmers' use of nonincome to purchase food, food assistance for asset programs, reliance on relief food, sale of livestock to purchase food, sale of forest products, reduction in the number of meals consumed daily, and the movement of herds between locations within the four agroecological zones. Analysis using a multivariate probit regression model revealed that various socioeconomic factors had diverse effects on the farmers' decision-making.Conferring to a study  in KituiAnother study conducted by  on the dThe research was carried out in Abay Chomen District, one of the districts of the Horo Guduru Wollega Zone, Oromia, Ethiopia. It is located about 295.1 km northwest of Addis Ababa, the capital of Ethiopia. Abay Chomen is bordered to the south by Lake Fincha (created when the Fincha Dam flooded the Chomen Swamp), to the southwest by Jimma Ganati and Horo District, to the northwest by Horo Bulk and Jarte Jardaga District, to the southeast by Guduru District, to the north by the Abay River, which separates it from the Amhara region, and to the northeast by Hababo Guduru . The capThis study uses a mixed-methods approach that combines qualitative and quantitative techniques. To comprehend a study problem, the blended approach entails gathering and analyzing several forms of data . The evan = the sample size, N = the study population, e = the level of precision (the acceptable sampling error) (assumed to be 8%), 1 =  the probability of the event occurring at the 95% confidence level.Because there was no document covering all rural homes in Abay Chomen County, multilevel cluster selection was utilized to select a sample. Agroecology was utilized as a stratifying variable since the study of rural livelihoods in Ethiopia is agroecologically sensitive. As a result, this study's sampling method was a stratified area-cluster sample design. As previously mentioned, the procedure began with the classification of the district into three agroecological zones: lowlands, temperate zones, and highlands. Based on data from the Abay Chomen District Agriculture and Natural Resource Bureau, seventeen rural kebeles have been divided into three agroecological zones. According to an unpublished document , there aAccordingly, Therefore, for this study 150 sample respondents were selected from those selected kebeles randomly .Descriptive statistics and econometric data analysis techniques were used in this investigation.The data collected from the households in the sample and other sources were analyzed descriptively. Descriptive statistics such as frequency distributions and means were used to describe the characteristics and distribution of strategies for livelihood.The factors of food insecurity and livelihood choices among farmers were studied using econometric models. The causes of food insecurity and the choice of livelihood alternatives in the district were investigated using logistic regression models and multinomial logistic regression models, respectively.(1) Determinants of Food Insecurity. For weighted average daily kcal adequacy per AE , the Federal Democratic Republic of Ethiopia's government has established a minimum demand of 2200 kcal AE . The threshold is used to differentiate between food-secure and food-insecure households. Food-secure or otherwise food-insecure households are those whose daily intake of kilocalories per AE  surpasses the subsistence line. The home food security status was the dependent variable, which had two values: 1 for food security and zero for food insecurity. Food insecurity is influenced by a variety of interconnected socioeconomic and climate variables, necessitating multidimensional analysis. The dependent variable, household food security status, is a binary variable. The logit model was used to estimate factors influencing food security status based on the results of the literature review. The cumulative logistic probabilistic model is specified as follows: Pi is the probability that an individual i is being food-secure given Xi (explanatory variables); α and β are parameters to be estimated. The logs of odd of the probability that an individual is being food-secure is given byIf an error term is assumed, the logit model is expressed asIn the case of a dummy dependent variable, OLS is not suitable for estimating the coefficient of the vector of parameters. Therefore, parameters were estimated using maximum-likelihood (ML) techniques. The maximum-likelihood method suggests choosing estimates of the values of the parameters that maximize the likelihood function. In many cases, it is a common practice to maximize the logarithm of the likelihood function itself, and the same results would be obtained.(1) Status of Household Food Security. The household's level of food security is a binary dependent variable with values of 1 for those that are secure in their food supply and 0 for those who are not. The grouping of households was caused by the compression between household AE  per day calorie consumption levels and the average AE  per day calorie consumption in rural Ethiopia, which was 2100 kcal/AE/day/person [y/person .(2) Choice of Major Livelihood Strategies and Its Determinants. This study, like most others, developed livelihood plans using income shares from each livelihood activity. The agricultural sector of respondents in the study area had three main sources of income, namely income from agricultural production; income from nonagricultural income-generating activities; and nonagricultural income. These categories of income included a different number of activities: income from agricultural production derived from the activities of staple foods, crops, and livestock; nonagricultural income from small businesses, rural handicrafts, remittance, food/cash, loans, and rent; and farm income derived from recruitment in various forms of employment opportunities such as work and others. For the purposes of this study, the following mutually exclusive combinations of livelihood security strategies were designed for the further analysis of the determinants of livelihood diversification in the study area: The second objective of this study, the choice of major livelihood strategies and factors influencing them, is described by four mutually exclusive livelihood strategies. The dependent variables have the following four nominal outcomes:y = 1): This major livelihood strategy included staple crop production, cash crop production, and livestock production.  Agriculture only (y = 2): The combination of agriculture and nonfarm livelihood strategy included agriculture plus petty trades (grain and fruit trade), rural craft, remittance, food/cash aid, loan, small ruminants, and cattle trade.  Agriculture plus nonfarm (y = 3): The combination of agriculture and off-farm livelihood strategy included agriculture plus daily labor work, other forms of hire either formal or informal, and natural resource-based activity .  Agriculture plus off-farm (y = 4): This livelihood strategy combined all activities mentioned above.  Agriculture plus nonfarm plus off-farm  assumption. Hence, the multinomial logit model is preferred for this study. To analyze the determinants of rural household decisions to engage in different livelihood strategies, the assumption is that in a given period, a rational household head is chosen among different mutually exclusive livelihood strategy alternatives that offer the maximum utility. Following , supposej in particular, then we assume that Uij is the maximum among j utilities. So, the statistical model is derived by the probability that choice j is made, which isUij is the utility to the ith respondent from livelihood strategy j, and Uik is the utility to the ith respondent from livelihood strategy k.If the respondent makes choice th household's decision can therefore be modelled as maximizing the expected utility by choosing the jth livelihood strategy among J discrete livelihood strategies.If the household maximizes its utility defined over income realizations, then the household's choice is simply an optimal allocation of its asset endowment to choose a livelihood that maximizes its utility. Thus, the ij categories, let the jth livelihood strategy that the ith household chooses to maximize its utility could take the value 1 if the ith household chooses jth livelihood strategy and 0 otherwise. The probability that a household with characteristics X chooses livelihood strategy j (Pij ) is modelled asIn general, for an outcome variable with J=0JPij=1 for any i, where Pij= probability representing the ith respondent's chance of falling into category j, X = predictors of response probabilities, and Bj = covariate effect specific to jth response category with the first category as the reference.with the requirement that ∑B1 = 0  so that exp(Xi′Bj)=1, implying that the generalized equation  model was used to explain the determinants of household livelihood decisions.Family size is a continuous variable that describes the size of the household's family unit.  It is poThe educational level of the head of household is a continuous variable measured in years of schooling. Education is a form of social capital that can have a positive impact on a household's capacity to make informed production decisions and nutritional status . Based oLivestock possession (excluding oxen) is a continuous variable measured by the number of tropical livestock units (TLU). Livestock is an important source of food and income for rural households. Households with more livestock produce more milk, milk products, and meat for direct consumption. Besides, livestock enables farm households to have a better chance to earn more income from selling livestock and livestock products, which enables them to increase their purchasing power of stable food during food shortages and could invest in purchasing farm inputs that increase food production and be able to ensure household food security . Thus, tThe number of oxen owned is a continuous variable that refers to the number of ploughing oxen. Oxen serve as a source of traction in many developing countries, thereby significantly affecting households' crop production. Animal traction power enables households to cultivate their own land and others' lands through renting, sharecropping, etc., and execute agricultural operations timely . This stThe frequency of extension contact is a continuous variable that involves a monthly visit by an extension agent. Frequent extension contact enhances households' access to better crop production techniques, improved inputs, and other production incentives, and these help to improve the food security status of households and participate in different livelihood strategies . Thus, tCultivated land size is an incessant variable that refers to the total cropping land cultivated by a household in the past one-year production period. A larger area of cultivated land implies more production and availability of food grains . Higher A dummy variable called “Credit Service” has a value of 1 if farmers have access to credit and 0 otherwise. Credit is readily available, which relieves cash shortages and enables farmers to purchase inputs such as fertilizer, better crop varieties, and irrigation systems. Due to the usage of agricultural inputs, which improve food production and ultimately raise household food security status, farmers who have access to finance would therefore have a favorable impact on crop production. That demonstrates the clear link between loans and the security of household food . TherefoOff-farm income, measured in birr, is a continuous variable that tracks the total amount of monetary income that any household member earns from jobs or other sources that are not related to farming.  As theirMonthly farm income is a continuous variable that measures the amount of income obtained from crop production and livestock rearing, measured in birr.  Noted thThe dependency ratio is the ratio of the economically active labor force (those aged between 15 and 65) to the economically inactive labor force (those aged between 15 and 65) . A largeAge in years is a continuous variable that represents the age of the head of the family. The social and physical settings, as well as farming activities, are significantly more richly experienced by older people . In otheA dummy variable, the gender of the head of the family, has a value of 1 if the head of the household is a man and 0 otherwise. According to Ref. , women mThe market's distance from the closest market centers is expressed in kilometers. Because off-farm employment dictates the income level of rural households, proximity to the nearest market may present a chance for increased income. Additionally, the farmer is more likely to obtain important information and buy agricultural inputs and finished goods needed for family consumption the closer he is to the market . As a reParticipation in selling livestock is a dummy variable taking a value of 1 if the farm household participated in selling livestock and 0 otherwise. Households that sell livestock are expected to fare better than their counterparts in terms of food security. This is due to the fact that selling livestock increases their revenue and decreases the risk of food insecurity that households can face. Hence, participation in livestock sales is hypothesized to have an effect on both households' food security status and their choice of livelihood strategies.A dummy variable called “fertilizer use” has a value of 1 if the farmer applies fertilizer and 0 otherwise. In order to increase farm production, chemical fertilizers such as urea and diammonium phosphate (DAP) are used. Utilizing fertilizer is frequently thought to increase farm yield per square foot . TherefoThere are five trigger means, such as demographic, institutional, infrastructural, technological, and income factors , by whicIn this study, the distinction between families with and without access to enough food is made based on the number of calories consumed by each adult daily at home. The household's calorie consumption is contrasted with the daily minimum suggested intake of 2100 kcal for adults . The household is categorized as having food insecurity if consumption or intake is below the advised quantity, and as having food safety if it is above the required amount. The food security status of households was measured through a direct consumption survey. The weighted technique was used to gather information on the kind and quantity of food consumed by the household over the course of seven days. Then, the data were transformed into kilocalories and then shared into household mass measured in AE  and number of days. Then, the amount of energy consumed in kilocalories for the household is compared with the subsistence level per adult and day .The result showed that of all households in the sample, 77 (51.3%) households were classified as food-insecure and 73 (48.7%) of them were classified as food-safe . The finThis result was deep-rooted by the study made by  on the aFarmers in the study area have used a variety of approaches to secure their livelihoods. A breakdown of the various livelihood security techniques used by households in the research area is provided below. Based on the analysis of the activity portfolios of households, approximately four different patterns of livelihood security strategies may be identified .The outcome of the descriptive statistics (pie chart) revealed that farmers in the research area most usually employ agricultural activities alone as a strategy for livelihood. About 29.3% of the sampled families relied solely on agricultural  activities for their means of subsistence. Additionally, roughly 26.7 percent of households relied on both farming and nonfarming occupations for a living. To make a living, farmers in the study region combined farming and raising cattle with off-farm pursuits including beekeeping, raising chickens, and working on other farms. On the contrary, agricultural and nonagricultural activities were used as a source of income in roughly 21.3 percent of the rural households in the research area. To make a living, they combined farming and ranching with nonagricultural pursuits including sporadic work and small-scale trading. Finally, in order to support their families, about 22.7% of the sample's households engaged in a mix of agriculture, nonfarm, and off-farm activities.P < 0.001). The result of the model estimation also showed that 9 of the 14 explanatory variables have a significant influence on the food security of households.To investigate the factors influencing rural families' food security status, a binary logistic model was applied. The model was chosen based on the rationale explained in the Methodology section above. Results of the binary logit model of the determinants of food security in households using data from a cross-sectional survey of 150 sample households are shown in As a result, only the household head's age, gender, family size, amount of cultivated land, number of livestock holdings, number of oxen owned, access to credit, involvement in selling livestock, and off-farm income were statistically significant factors in determining a household's food security status . TherefoWith a probability of 5%, this variable has a negative and significant impact on the food security status of households in the research area. The odds ratio for the head of the household revealed from the model's results that the food safety was reduced by a factor of 0.0489 for every year that the household head's age increased. This suggests that older household heads are more likely than younger ones to experience food insecurity. This is because older household heads are less productive and lack the confidence to manage larger farms than their younger counterparts. In addition, older households could not participate in other income-generating activities. On the contrary, older households have large numbers of families and their resources have been distributed among their members. This result is in line with the findings of Refs. , 23.In line with the expectations of the study, it was discovered to have a positive and significant impact on the food security status of households at a level of significance of 5%. From the model result, the odds ratio of the variables showed that households with male bosses increase the households' food safety by a factor of 1.5912. This implies that households with male management are more likely to be food-safe than households with female management. This is due to the fact that mostly male-headed households have better access to different types of resources, which gives them the opportunity to buy and consume the products they want. This result is in conformity with the findings of Ref. .As expected, the family size of the heads of households was found to have a negative impact on the food security status of households at a level of significance of 1%. As indicated in the table above, the odds ratio of the family size showed that an additional person in the household reduces food safety by a factor of 0.3499. This suggests that a larger family size compared with a smaller family size in the study area tends to indicate food insecurity. This is because households in rural areas with large family sizes, composed mostly of nonproductive members, could struggle to maintain food security, and, ultimately, due to the high stress on the active workforce and the lower availability of food to each person in the household end up struggling to achieve food security .The variable was discovered to be associated with the household's level of food security and to have a significance level of 10% when it came to influencing the dependent variable. According to the model output's chance ratio for acreage size, a household's food security is increased by 0.0672 for every additional hectare of land. Greater output and availability of food grains are implied by a greater cultivated area . IncreasAt a level of significance of 1%, it was discovered that raising farm animals is positively and significantly associated with households' food security status. The model's output revealed that the odds ratio of livestock ownership increased by a factor of 0.2778 for every additional unit of tropical livestock in the household. For rural households, livestock is a significant source of food and money. For immediate consumption, households with more cattle produce more milk, dairy products, and meat. Additionally, livestock farming provides farm households with better chances to increase their income from the sale of livestock and livestock products, allowing them to increase their ability to purchase stable food during food shortages and to invest in the purchase of agricultural inputs that boost food production and can ensure household food security [As expected, the number of ox owners was found to be positive and statistically significant, with a significance level of 5%. From the model output, the odds ratio of the variables showed that having an additional number of oxen in the household increases food security by a factor of 0.3745. Oxen are used as a source of energy and thus have a considerable negative impact on household crop production in many developing countries. The animal traction enables households to farm their own land and others' lands through renting, sharecropping, etc., and carry out agricultural activities on time .As expected, this variable has a positive and significant influence on the food security status of households at a significance level of 1%. From the model result, the odds ratio of the variables shows that access to credit increases household food security by a factor of 1.7217. This implies that households that have had access to credit services are more likely to have a safe diet than households without access. This is because lending enables households to participate in income-generating activities, so the income generated increases the household's financial standing and purchasing power to avoid the risk of food insecurity. Additionally, it helps to smooth out consumption when the household is faced with temporary food problems. This result is confirmed by the results of Ref. .It was found that the sale of livestock has a positive and significant impact on the food security status of households at a level of significance of 1%. From the output of the binary logit model, the odds ratio of the variables shows that selling livestock increases the probability of household food security by a factor of 1.5609. The result implies that households that sell livestock have a greater chance of food safety than their counterparts. This is because selling livestock increases their income and reduces the risk of food insecurity for households .Contrary to predictions, it was discovered that this variable, at a level of significance of 10%, had a negative and significant impact on the food security status of households. The odds ratio supported the binary logit model's finding that a one birr increase in nonagricultural household income lowers food safety by a factor of 1.5896. This shows that households in the study area with low earnings are more likely to have food security than households with greater nonagricultural incomes. This outcome is consistent with that of Ref. .The factors that influence a rural household's decision about its mode of subsistence were determined using the multinomial logistic model. The model study analyzed the other options as alternatives to this option and simply depended on agriculture  as the basic category for no diversification . The oveThe level of education of the household head had a positive and significant influence on the use of agriculture (on-farm), nonagricultural and agricultural (on-farm), and nonfarm strategies to secure a livelihood with a probability of 5% and 10%. That is, if all other factors remain the same, every extra year of education raises the likelihood of employing techniques for a living that combine farming and nonfarming by 2.32 percent and 1 percent, respectively, and 37 percent as compared to just the most fundamental sector of agriculture (on-farm) . This isIt was found that this variable has a positive and significant influence on the choice of household livelihood strategies for securing a livelihood in and outside the company with a probability of 5%. A household's likelihood of engaging in agricultural and nonfarm activities has improved by 3.45 percent, according to the model's results, while access to credit has increased by 25.79 birr, all other parameters being held constant . This isAt a significance level of 10%, it had a favorable and substantial impact on the usage of a combination of on-farm, off-farm, and nonfarm livelihood methods. Ceteris paribus, this implies that a 1 TLU increase in animal husbandry improves the likelihood of using a strategy for the agricultural operation + external plus nonagricultural operations as the basis of life by 23.69 percent compared with the benchmark alternative simply on the farm . This isIt was discovered that the number of oxen owned, at a level of significance of 5%, had a favorable and significant impact on the combined use of livelihood methods such as on-farm, off-farm, and nonfarm. The outcome reveals that, when all other factors are held constant, an increase in the number of oxen possessed by 1 ox decreased the likelihood of relying solely on farming for a living by 29.09 percent compared with the base category-only farm yard.The variable has a negative and significant impact on households' decisions in favor of the diversification approach for agricultural and nonagricultural livelihoods, with a likelihood of less than 1%. According to the model's marginal effect, ceteris paribus, there has been a 173.84% decline in the likelihood that a household will utilize an agricultural (on-farm) plus nonfarm strategy. This is due to the fact that households located far from the market center lack access to knowledge about engaging in nonagricultural activities, which has led to a fall in livelihood and livelihood strategies .As expected, this variable has a positive and significant influence on households' choice between farms (agriculture only) plus off-farm, farm plus nonfarm, and a combination of farm, off-farm, and nonfarm diversification strategies for agricultural livelihood with a probability of less than 5%, 5%, and 10%, respectively. With otherwise constant factors, the result of the model results in the marginal effect that the probability that a household will be used in-house plus outside, in-house and outside of the company, and a combination of in-house, off-farm, and nonagricultural activities. The activities increased by 0.001%, 0.001, or 0.0005% among farm households whose monthly income increased by 0.02 birr . This isPoverty and food insecurity are significant issues that the majority of Ethiopians currently face. Both chronic and temporary  food insecurity are acute across the nation. According to several research papers, improving the lives of the rural poor will be crucial in reducing the occurrence. Therefore, every endeavor to improve the lives of the rural poor and their livelihood strategies must include an assessment of the food security status, the livelihood strategies, and their determinants by taking into account food security dimensions at the household level. In order to examine rural households' levels of food security, their means of subsistence, and the factors that influence their decision to avoid food insecurity, researchers looked at Abay Chomen District.Data from 150 sampled household heads who were interviewed on a set schedule were used in the study. In order to shed light on the many socioeconomic features of farmers, their level of food security, and the differences between households with and without food security, descriptive statistics  were utilized. The study also used a binary logit model and a multinomial logistic regression model to examine household livelihood strategies, food security status, and their respective factors.The study's findings indicated that, in the study region, 51.3% of the tested households experienced food insecurity, while 48.7% did not. This suggests that there was a food insecurity problem in the research area for more than half of the examined households. The report also showed that the sampled families' average daily calorie consumption was 2008.54 kcal per adult equivalent, which is less than the recommended minimum of 2100 kcal. The report also showed that the range of calorie intake was between 4186.98 and 697.69.To investigate the factors influencing the level of food security in rural families, a binary logistic model was estimated. The model's findings supported the notion that a household's level of food security was significantly influenced by the head of the household's age, gender, family size, amount of cultivated land, number of livestock holdings, number of oxen owned, access to credit, involvement in livestock sales, and off-farm income. To investigate the households' choice of rural livelihood strategy, a multinomial logistic model was estimated. In light of this, the household's choice of livelihood methods was significantly influenced by the household head's education level, livestock holding, number of oxen possessed, access to finance, distance to market, and monthly farm income.The coverage of the study area was primarily responsible for this study's limitations. Due to time and money constraints, the investigation was limited to Abay Chomen District. A cross-sectional household survey was conducted because there are not many of the time series or panel data needed to measure food security in the research area. The study could only use cross-sectional data as a result.Based on the evidence obtained from this finding, there is a need for urgent action aimed at addressing the need for improving the food security status of rural households to enhance their well-being and to reduce the consequences of different shocks in the study area. These may include the following:Since the gender of the household head is one of the variables that affect rural households' food insecurity status, improving female-headed households' knowledge and access to different livelihood assets to improve the food security status of the rural poor should be prioritized, because families led by women are more impacted by a lack of information than households headed by men.The creation of awareness for the elderly should be reinforced because the age of the family head affects food security. Therefore, it is important to provide old household heads with capacity building so that precise information may be made available and spread, allowing them to increase production and ensure food security.As access to credit affected food security status positively, future interventions should focus on improving rural household's access to credit, because access to credit helps rural households to purchase different inputs to improve their production and consumable products and thereby helps them to ensure food security and improve their well-being. Therefore, development partners operating in the study area should implement provision of credit to eligible households using targeting criterion that reflects actual characteristics of households.As farm income affected the choice of livelihood strategy positively, future interventions should focus on improving farmer's farm income-earning opportunities. Therefore, it is important to emphasize adequate input supply as a policy option for guaranteeing food security because it boosts farm revenue in rural areas.Even though it is presumed that easier access to markets will result in lower transportation and other market-related transaction costs, study results show the contrary. Therefore, raising farmers' awareness of the value of improved market access on their ability to make informed decisions about the type of output to be produced, the kind of inputs and products to be purchased in the market, etc., aids farmers in improving their current state of food security in the near future.In general, this study has sought to produce the outcome of the analysis within a given scope, but there are still many questions that need to be addressed. Future researchers must pay close attention to provide fundamental knowledge on the social, political, natural, and environmental dimensions that determine food security status and livelihood strategy choice, descriptive data on food insecure purchasing patterns, and specific traits that make rural poor more vulnerable to food insecurity.


Despite numerous studies on the neurobiology of depression, the etiological and pathophysiological mechanisms of this disorder remain poorly understood. A large number of animal models and tests to evaluate depressive-like behavior have been developed. Chronic unpredictable mild stress (CUMS) is the most common and frequently used model of depression, and the sucrose preference test (SPT) is one of the most common tests for assessing anhedonia. However, not all laboratories can reproduce the main effects of CUMS, especially when this refers to a decrease in sucrose preference. It is also unknown how the state of anhedonia, assessed by the SPT, relates to the state of anhedonia in patients with depression. We analyzed the literature available in the PubMed database using keywords relevant to the topic of this narrative review. We hypothesize that the poor reproducibility of the CUMS model may be due to differences in sucrose consumption, which may be influenced by such factors as differences in sucrose preference concentration threshold, water and food deprivation, and differences in animals’ susceptibility to stress. We also believe that comparisons between animal and human states of anhedonia should be made with caution because there are many inconsistencies between the two, including in assessment methods. We also tried to offer some recommendations that should improve the reproducibility of the CUMS model and provide a framework for future research. According to the World Health Organization, more than 280 million people of all ages suffer from depression. Less than half of them receive appropriate treatment for their disorder, and, in low- and middle-income countries, 75% of people receive no treatment at all . The preThe development of depression is determined by a combination of genetic and environmental risk factors. The heritability of liability to major depression is estimated at 30–50% ,12,13. HOur society is facing a great problem, and scientists are, in the words of Eric J. Nestler, in a Catch-22 situation (a vicious cycle from which it is impossible to get out). We need animal models to better understand the pathogenesis of depression, but the animal models are difficult to develop without understanding the pathophysiology of the human disorder ,21.R. Porsolt, who proposed the forced swimming test in 1977, began his article with the following words: “A major problem in the search for new antidepressant drugs is the lack of animal models which both resemble depressive illness and are selectively sensitive to clinically effective antidepressant treatments” . This stThe CUMS model of depression is one of the best attempts to simulate the human state in animals. It is the most common and frequently used model of depression, and the sucrose preference test is one of the most common tests for assessing anhedonia in rodents. However, the difficulty of reproducing this model by different laboratories and the low reproducibility of the results impose restrictions on the use of the CUMS protocol. Completely different factors can be the source of poor reproducibility. In this review, we attempted to identify factors that might influence CUMS reproducibility and started with factors that may affect sucrose consumption .Original articles and reviews were searched using the PubMed database. To search for articles, the following keywords were used in various combinations: sucrose, preference, consumption, concentration threshold, chronic unpredictable mild stress, depression, anhedonia, water deprivation, food deprivation, stress-susceptible, stress-resilient. We deliberately tried to refer to primary sources, even if they were published many years ago, to avoid incorrect or ambiguous interpretations of the results. In this regard, we did not limit the search for literature to any particular period of time. Articles published more than 10 years ago were additionally analyzed in the Scopus database for newer articles, looking through all documents citing this article . For each selected article, the title and abstract were analyzed for relevance to the topic of this narrative review. Since one of the goals of the review was to compare data obtained in experimental animals with data obtained in humans, we analyzed experimental articles on both animals and humans.There are several models of depression  and tests to evaluate depressive-like behavior  ,29,30,31The chronic unpredictable mild stress model is one of the most widespread and commonly used animal models of depression. For the first time, chronic stress was proposed as a model of depression in 1982 by R. Katz, who acted in an unpredictable order on animals for 3 weeks by a set of stressful factors, such as unpredictable shock, cold swim (+ 4 °C), water and food deprivation, heat stress (+ 40 °C), shaker stress, and reversal of day/night cycle, and found a decrease in the consumption of sucrose solution by animals, which was interpreted by the author as a hedonic deficit . SimultaPeople are constantly exposed to uncontrollable multimodal stress factors, whose nature, strength, and the probability of which they cannot predict. Strong infrequent life events and relatively weak daily hassles can both provoke the development of depression . FactorsIn 1986, Chappell P. et al., in their work, mitigated the strength of stressful factors and modified the protocol proposed by R. Katz using isolation housing, cold swim (0 °C), increased housing density, tail-pinch, double housing with unfamiliar cagemates, reversal of light/dark cycle, cold immobilization at 15 °C, food deprivation, and ether stress . In 1987CUMS in rodents causes various physiological changes : sleep dOne of the main consequences of CUMS is anhedonia, the inability to experience pleasure, a condition that is often assessed in rodents by their preference for sucrose solution. Currently, according to P. Willner, there are more than 1300 publications in which CUMS was used, and, every year, the number of laboratories that use CUMS is growing. For example, in 2015, CUMS was mentioned in 230 publications and used by 180 laboratories from 30 countries . HoweverAs with any other model, CUMS has its pros and cons. The main advantages of CUMS are unpredictability and uncontrollability. The strength of the model is its naturalistic character, which best reflects the duration of exposure and the strength of stressful factors. The model’s advantages also include the long-term maintenance of induced disturbances (stability of effects), a property that allows testing drugs with a chronic administration regime and identifying therapeutic compounds with a fast mechanism of action ,55. AmonCriticism from a number of researchers regarding the CUMS model is directed not so much at the procedure itself, whose effectiveness on the physiological state of the animal is obvious, but at the appropriateness of using the sucrose preference test as a measure of anhedonia and depression-like behavior and the possibility of extrapolating results obtained in animals to the state of anhedonia in humans. There are some inconsistencies between rodent and human studies predominantly associated with anhedonia . This isIt is now accepted that reward includes such subcomponents as wanting, liking, and learning ,67,68, bThe concept of anhedonia, proposed in 1886 by T. Ribot as an inability to experience pleasure, is now largely revised. Currently, anhedonia can also be divided into several subtypes, such as consummatory anhedonia (deficits in the hedonic response to rewards) and motivational anhedonia (diminished motivation to pursue rewards) .Based on the nature of the rewarding stimulus in humans, at least three subtypes of anhedonia can be distinguished. Physical anhedonia is characterized by the inability to experience pleasure from eating food, touching, sex, temperature, movements, smells, and sounds. Social anhedonia is associated with the inability to experience pleasure from being with people, talking, exchanging expressions of feelings, doing things with them, competing, loving, and interacting in other ways. The third type of anhedonia is associated with intellectual pleasure, the pleasure of achievement and pleasure from art and music . HoweverAnhedonia and depressed mood are the main symptoms of depression, and the presence of one of them is a necessary condition for making a diagnosis in humans. Of these two symptoms, only the state of anhedonia seems possible not only to simulate but also to evaluate in experimental animals.Anhedonia is currently assessed using appropriate medical scales for humans ,77,78,79In the case of using behavioral tests to assess anhedonia in humans and animals, the type of reinforcing stimuli in these tests has a significant difference. In experimental animal studies, the so-called primary reinforcing stimuli  are used, which are instinctive and inherited. In clinical studies on patients, researchers usually employ secondary rewards acquired in the learning processes  . In thisThe complexity of the concepts of anhedonia and reward is obvious; however, when working with experimental animals, researchers usually operate with the disturbances in the «liking» subcomponent (consummatory anhedonia), while neurobiological studies on humans focus mainly on the disturbances in the «wanting» subcomponent . It can be assumed that, as a result of CUMS, physical, consummatory anhedonia develops, and we evaluate the hedonic response or liking. However, in this case, in our opinion, it is not correct to extrapolate a particular case of disturbance in hedonic behavior (in one of the subcomponents of reward) in animals to the human state of anhedonia, which can be more complex and multifaceted. Hayward M. interprets the two-bottle test as a measure of consummatory behavior (liking) and the progressive ratio schedule of reinforcement as a measure of appetitive behavior (wanting) . InteresThe use of different reinforcing stimuli in humans and animals makes direct comparison of results difficult. Additionally, at present, there is no clear understanding of how behavioral reactions to primary and secondary reinforcing stimuli relate to each other.The question of the appropriateness of using the sucrose preference test also arises when trying to use its analog (sweet taste test) in a clinical setting. No disturbances were observed in the preference for sucrose solution in patients suffering from depression ,99, and There are also no convincing answers to other questions regarding anhedonia: is anhedonia the main symptom of depression in humans? Is the inability to experience pleasure a condition typical of depression, or is it a personality trait? How specific is anhedonia to depression? Is the symptom of anhedonia homogenous or heterogeneous ? Although anhedonia is one of the main symptoms of depression in humans, it is observed in only 37% of patients . AdditioIt is now clear that anhedonia is not a symptom specific only to depression but is also usual for other mental disorders ,117, incIn the sucrose preference test, researchers usually employ a 1% solution a priori, which is not always optimal under specific conditions. The concentration of the solution should be minimal but at the same time sufficient for the preference of the solution by animals.An analysis of sucrose preference in the concentration range from 10 mM to 100 mM among 14 different rat strains indicated a high degree of preference for the sweet solution in animals of all strains and the absence of significant differences between them . HoweverRats are characterized by individual differences in the consumption of 1% sucrose solution. The consumption of sucrose solution by animals with the highest and lowest levels can differ by more than two times. Simultaneously, animals do not differ in the level of sucrose preference . AccordiThe dependence of the preference for a sweet solution on age in animals is minimal. A decrease in the sucrose preference can be observed only in rats aged 69–72 weeks , and theSucrose consumption in rats has an inverted U-shape. Water consumption is minimal when there is a sucrose solution in a concentration range from 0.4 to 30%. The maximum consumption of sucrose solution is observed at a concentration of 8% . The conSince the exact threshold of preference for the sucrose solution has not been established and may depend both on the state of the animals and on other factors , it seems reasonable to determine the optimal concentration of the sucrose solution before the implementation of the CUMS protocol. A preliminary determination of the dependence of the preference on sucrose concentration can significantly increase the discriminatory sensitivity of the test. Criticism related to the appropriateness of using the sucrose preference test as a measure of hedonic behavior arises not only when extrapolating this test to humans but also when directly assessing the depressive-like state of animals exposed to CUMS. Initially, a number of researchers pointed to the fact that, when adjusting the sucrose consumption to the body weight of the animal, the effect of CUMS on sucrose intake disappears. Simultaneously, it was suggested that body weight largely determines the consumption of sucrose solution by animals, and that weight loss, due to food deprivation, significantly affects the consumption of sweet solution ,152. ForIt is likely that food deprivation, which results in hunger and a slowdown in body weight gain, can really affect the consumption and preference of palatable solutions, but the relationship between these processes requires a separate detailed investigation. Cabanac M. proposed the term alliesthesia, conferring the dependence of the pleasantness/unpleasantness of an external stimulus for an organism on its practical usefulness, determined by the internal state of this organism ,160. AccHunger caused by food deprivation affects the reward and can have a distorting effect on the interpretation of the results. In other words, the consumption of sucrose solution is determined by hunger on the one hand and the feeling of pleasure from sucrose consumption on the other. In the case of food (and/or water) deprivation, motivation associated exclusively with hunger has a great influence on the consumption of a sweet solution. The sated animal consumes a sweet solution mainly for its pleasurable or rewarding properties and a food-deprived animal mainly due to metabolic/energy needs. Food deprivation enhances the motivation to obtain food in animals, and the consumption of food under such conditions is pleasure by itself. Rats consume more sucrose pellets following food deprivation for 24 h. Under a progressive ratio schedule of reinforcement, rats have a higher break point when they were food deprived compared to food sated . As with food deprivation, water deprivation can have a significant effect on the consumption of a sweet solution by animals. For example, it was shown that a decrease in saccharin intake and preference in rats exposed to CUMS is observed only after water deprivation . This efDespite the possible shortcomings, water and food deprivation are the most commonly used stressful factors in CUMS . Due to Along with numerous data showing a decrease in sucrose consumption/preference, some authors indicate the absence of any changes in consumption , even inIt has been shown that people increase their consumption of palatable foods during chronic stress ,182. DepIt becomes clear that animals can either reduce, not change, or increase the intake of palatable solutions during CUMS. Moreover, discrepancies between laboratories are not necessarily related to the design of the experiment but rather are explained by the individual features of the animals. In particular, it was shown that some animals from one batch exposed to CUMS reduced their sucrose consumption, others did not change it, and a third portion even increased their consumption ,194. We Many researchers are actively discussing the individual susceptibility of an organism to stress factors. Some people successfully adapt and cope with the negative consequences of adverse effects, while others, on the contrary, become more susceptible to the development of psychopathology. A similar phenomenon has also been found in animals. It has been established that even animals of the same strain, coming from the same source, having the same sex, age, and under identical housing conditions, react differently to stressful stimuli and are divided into stress-susceptible and stress-resilient.Numerous studies have shown that animals belonging to different groups (stress-susceptible and stress-resilient) under stressful conditions change their consumption of sweet solutions differently. It is difficult to predict how many animals belonging to one or another group will be in a particular batch. According to some researchers, 70% of animals exposed to CUMS reduce their consumption of sucrose solution, and the remaining 30% do not change their consumption ,196,197.The segregation of animals into stress-susceptible and stress-resilient occurs with different types of stress and is not limited to CUMS. In particular, such a distribution is observed, for example, in social defeat, where only stress-susceptible animals reduce their sucrose preference . LearnedIt should be noted that stress-resilience is an active process of adaptive maintenance of normal physiology under the action of stressful factors, which is based on the coordinated activity of all systems of the organism ,205. TheBy applying the CUMS model, researchers often use the concepts of “stress-susceptibility” and “stress-resilience”. Along with this, two more terms are common in the literature: “animals with an enhanced response (high responders (HR))” and “animals with a weakened response (low responders (LR)”. In our opinion, these definitions are very close and reflect the same phenomenon: the type of response of the organism to the stress factor. Just as stress-susceptible and stress-resilient animals differ in their consumption of sweet solutions, high responders differ from low responders in depressive-like behavior. In particular, animals pre-segregated based on their locomotor activity in a novel environment (into groups of high and low responders) differ in their depressive-like behavior in the forced swim test , forced It is obvious that animals in every particular batch are not equal and react differently to the same stressful factors. Without preliminary segregation of animals into stress-susceptible and stress-resilient groups, some effects induced by stress  can be more or less “diluted” depending on the percentage of stress-susceptible and stress-resilient animals in the group. This, in turn, can lead to the poor reproducibility of some CUMS effects.In preparing this review, we were surprised by the lack of studies discussing the poor reproducibility of the CUMS model, studies directly comparing the state of anhedonia in animals exposed to CUMS with the state of anhedonia in humans with depression, and studies comparing various tests to assess the state of anhedonia in animals. The overwhelming majority of studies related to sucrose consumption in rodents were published more than 30 years ago and have not been confirmed by modern approaches. The CUMS model of depression is one of the best attempts to simulate the human state in animals. However, the difficulty of reproducing this model by different laboratories and the low reproducibility of the results impose restrictions on the use of the CUMS protocol. Different factors can be the source of poor reproducibility, such as suboptimal concentration of sucrose solution, water and food deprivation, and differences in stress susceptibility. There are some inconsistencies between rodent and human studies, predominantly associated with the assessment of anhedonia-like differences in reinforcing stimuli and a discrepancy between the sweet taste test and a sucrose preference test. The main issue is the appropriateness of using the sucrose preference test for the evaluation of depressive-like behavior and anhedonia. This test is very common and easy to perform. However, there are still many questions related to its employment. Is sucrose preference a measure of anhedonia? If so, which of the subcomponents of reward and which subtype of anhedonia do we evaluate? Is a change in the sucrose preference a reflection of a depression-like state or may it be associated with other processes? How do the changes in sucrose preference in animals correlate with the lack of changes in similar tests in humans? Is it possible to extrapolate the results obtained in animals to the state of anhedonia in humans? Why does a change in sucrose preference in existing cases not correlate with a change in the threshold of intracranial self-stimulation? We still have to answer not only these but also many other questions regarding the neurobiology of depressive disorder and experimental modeling of depressive state in animals.We can offer the following main recommendations regarding the use of the sucrose preference test aimed at improving the reproducibility of the CUMS model:(1)Determine the minimal  concentration of the sucrose solution before the CUMS.(2)Determine the basal level of sucrose consumption/preference before the CUMS to identify animals with low, high and/or unstable sucrose consumption.(3)To minimize the influence of metabolic factors on animals’ sucrose preference, it is advisable to exclude water and food deprivation from the protocol or evaluate sucrose preference not earlier than 24 h after deprivation.(4)Before starting the experiment, it is advisable to segregate animals into groups with high and low responses to stressors .A deep study of the following questions seems to be very interesting:(1)Analysis of sucrose consumption (2)Comparison of different tests for assessing anhedonia in animals with each other.(3)Revealing reward subcomponents that are actually impaired in depressed patients and animals exposed to CUMS(4)Characterization of anhedonia subtypes, which develop in depressed humans and animals exposed to CUMS(5)Studying the regulatory effects and mechanisms of action of palatable food on HPAA functioning during CUMS(6)Studying the relationship between hunger (food deprivation) and sucrose solution consumption by rodents.


Guillain-Barrè syndrome (GBS) is an acute immune-mediated disorder affecting peripheral nerves and nerve roots with a variable clinical course and outcome. Epidemiologic analyses have revealed that the incidence of the syndrome increases linearly among the age. The clinical diagnosis of GBS is based on the family history, physical and neurological examination, electrodiagnostic exams, and cerebrospinal fluid analysis with the classical presence of albumin-cytologic dissociation. Prognosis is associated with the severity of clinical signs and the type of peripheral nerves involved.This study aims to clarify which clinical features can be used for prognostic purposes. We evaluated the correlation between (1) brain MRI lesions and grade of disability; (2) brain MRI lesions and elevated cerebrospinal fluid (CSF) protein; and (3) increased levels of CSF protein and grade of disability. Statistical analysis extracted from these data indicated a good correlation to be a prognostic indicator in children affected by GBS. We found little evidence regarding laboratory tests, imaging, and prognosis. We enrolled 12 continuous patients who met the Brighton criteria for GBS in this retrospective study. Each patient was clinically evaluated at the time of disease onset to assess the GBS disability score and after 2 weeks.r-value of 0.87. The values suggest a correlation among the MRI score, CSF protein, and prognosis.We estimated Pearson's correlation index to evaluate the possible correlation between MRI and disability and CSF protein levels and disability. The correlation coefficient was 0.92 and 0.85, respectively. In addition, we developed a graph to see the trend of the disability values, proteins in the CSF, and damage assessed with MRI in the 12 patients. It seems that these parameters have a parallel trend and a good correlation in each patient. Finally, we calculated the correlation between MRI and CSF protein values, with an The MRI and CSF laboratory parameters can be important tools for the clinician not only for diagnosis but also to evaluate the possible worsening of general conditions or the need to prepare measures to support life parameters. Patients who need ventilatory support could be established early from patients who have less severe GBS and can begin rehabilitation earlier. We suggest MRI should be performed routinely in children with GBS to be able to estimate the evolution of the clinical condition. Guillain-Barrè syndrome (GBS) is an immune-mediated rapidly developed polyneuropathy whose etiology and pathogenesis are not yet entirely comprehended. Guillain–Barré syndrome (GBS) manifests clinically as acute flaccid paralysis, marked by the symmetrical weakness of the limbs, and hyporeflexia or areflexia, which arrives full harshness within 4 weeks .Sensory symptoms, such as paraesthesia or insensibility, begin distally and have a symmetrical extension.Among pediatric patients in the zenith phase of the syndrome, 75% are unable to walk unsupported, 30% are quadriplegic, 35–50% show cranial nerves involvement, and 15–20% have respiratory failure and/or autonomic dysfunctions .Epidemiological analyses have documented that the incidence of GBS increases with age. In children from 0 to 9 years, it occurs with an incidence of 0.62 cases per 100,000 person-year (py) , 6.Diagnosis of GBS is based on the patient's family history, physical and neurological assessment with sensorial and motor disturbances, electrodiagnostic exams, and cerebrospinal fluid (CSF) which reveals the classical pattern of albumin-cytologic dissociation.The prognosis of the GBS is linked to the severity of clinical signs and unclear to the presence of autonomic nerve dysfunction . PredictWe evaluated the correlation among CSF analysis, imaging, and the severity of the GBS in the acute phase to predict a short-term outcome.We aimed to evaluate CSF analysis and imaging to determine the severity of the GBS in the acute phase and to predict a short-term outcome.We evaluated the possible correlation among MRI radiological classification, the values of proteins in the CSF, and the prognosis of children with GBS.The correlation between the increasing values of the radiological classification of the clinic with the GBS disability score and the prognosis was evaluated.In addition, we evaluated the correlation between increasing CSF protein levels and symptomatology and prognosis.A systematic revision of the current literature was conducted using Cochrane, EMBASE, and MEDLINE. In addition to official websites of highly qualified journals which were expected to publish studies related to this topic, for example, the New England Journal of Medicine, The Lancet, PLOS Medicine, Neurology, and Pediatrics were also searched for relevant studies. The words used to search were: “Child; Guillain-Barrè; Neurology; Prognosis; Disability; Laboratory; MRI; cerebrospinal fluid.” We found little evidence regarding laboratory tests, imaging, and prognosis. Following, we cite the most recent evidence regarding prognosis and imaging and prognosis and CSF.Althubaiti et al. in a recent publication on the prognosis value of MRI in children with GBS advise that brain and spinal MRI is a recommended supportive test but a predictive value for clinical and therapeutic outcomes in the short or long term has not yet been proved .Regarding the proteins in the CSF, we want to mention the most recent evidence proposed by Kasser et al. In their letter to the editor, the authors affirmed CSF protein levels seemed to be potentially associated with the need for mechanical ventilation .The Guillain-Barré syndrome (GBS) disability score is a widely accepted scoring system to evaluate the functional level of patients with GBS. It was originally described in Hughes et al.  and sincThe patient's level of disability is reported operating on a scale from 0 to 6: Grade 0 is assigned to the asymptomatic patient; Grade 1 is associated with movement reduction but capable of performing manual work; Grade 2 is assigned to those who walk but are unable to perform work with their hands; Grade 3 concerns patients who need support for walking; Grade 4 is assigned to patients who are bedridden. The last 2 degrees of the disease in which there is respiratory failure or death . The GBSThe Erasmus GBS and van Koningsveld et al. –12 evaluMagnetic resonance (MR) imaging also contributes to the diagnosis of GBS by demonstrating anterior and posterior intrathecal spinal nerve roots and cauda equine. Gorson et al.  showed aWe evaluated the chemical-physical characteristics of the CSF in each child, examining appearance, color, number of cells, glucose, proteins, presence of immunoglobulins, and albumin. We examined all these parameters one by one for their correlation with the GBS disability score and therefore with the prognosis.In this study, the levels of CSF proteins were evaluated according to the increases of 1, 2, and 3 times the basal cut-off value of 45 mg/dl.The manuscript attempts to evaluate whether a clinical score (the grade of disability of patients), an imaging score , and a grade of albumin-cytologic dissociation in CSF are linearly correlated to give a prognostic value of the disease.We retrospectively enrolled 12 continuous children affected by GBS and diagnosed at the Clinical Pediatrics Department for 10 years from January 2012 to January 2022 . The chiClinical: each patient was clinically evaluated at the time of disease onset assessing the GBS disability score and after 2 weeks. In addition, all the children treated in our center were placed in instrumental clinical follow-up by carrying out checks at 2 weeks to 1 month, 3 months to 6 months, and 1 year from the onset of the disease. In this study, we collected clinical data at onset and 2 weeks after onset .Imaging: all patients enrolled in this study underwent MR of the brain and spinal cord. Images were evaluated and classified by the pediatric neuroradiology team and assessed by Yakilmaz radiological classification .Laboratory: lumbar puncture (LP) was performed on average 3 days after symptom onset , and allPatients selected during this period were treated according to guidelines with standard IVIg administration of 1 g/kg daily for 2 days. In addition, patients with clinical follow-up at 2 weeks were included in the study. Data were collected and a statistical analysis was done to determine the presence of a possible correlation among these three variables.We performed a statistical analysis to measure the potential relationship between the clinical progress of children with GBS, MRI imaging, and CSF protein levels. We measured the correlation index between the clinical and assessed and the GBS and MRI scores according to Yakilmaz Classification. We observed that the CSF parameters that correlated with GBS disability score at 2 weeks were protein levels in the CSF, when these were increased 1, 2, and 3 times the cut-off value of 45 mg/dl as Kerasnoudis et al. reported .We performed an extensive literature search and found no publications evaluating a possible correlation among the clinical severity of GBS, imaging, and laboratory values of CSF proteins combined in the same population.Two children showed notable signs of respiratory impairment and were intubated. Three children showed involvement of the cranial nerves. Children with respiratory disturbances involving the cranial nerves had a worse clinical course . TriggerWe executed the statistical analysis to measure the potential relationship among the clinical assessment of children with GBS, MRI imaging, and CSF protein levels.r calculated for all correlations are close to unity and therefore indicate a strong correlation value between them. We developed a graph to see the trend of the disability values, proteins in the CSF, and damage assessed with MRI .It seems that these parameters have a parallel trend and a good correlation in each patient. The values of R2 = 0.8573).The graph  shows thWe assessed the chemical-physical characteristics of the CSF in each patient: appearance, color, the number of cells, glucose, proteins, presence of immunoglobulins, and albumin.We examined these parameters one by one and the correlation with the GBS disability score and the prognosis.The single parameter showing the more robust correlation with prognosis was the increase of the proteins in the CSF.R2 = 0.7342).The graph  shows thOur pediatric neuroradiologists team evaluated and classified magnetic resonance images following the Yakilmaz radiological classification . This clThe graph  reports The graph  was perfStaging the pediatric patient affected by GBS assumes an important value both in the general evaluation of the patient and in the prognosis. Currently, prognostic scores are based exclusively on clinical parameters, such as the GBS disability scale and the Erasmus GBS scale. There is no clinical-prognostic score that takes into consideration radiological or laboratory parameters.To fill this gap, we tried to evaluate the correlation between the imaging staging of GBS on MRI and the chemical-physical examination of the CSF of 12 pediatric patients treated.In our evaluations, we were able to evaluate a good correlation between them.We assessed that MRI should be considered an essential and effective exam in the diagnostic and prognostic evaluation process in GBS. The involvement of the anterior and posterior nerve root is associated with severe clinical conditions and, consequently, with a worse prognosis .Brain MRI then should be performed routinely in children with GBS to estimate the possible evolution of the clinical condition.Regarding the CFS analysis, we observed that among the various elements of cerebral liquor, the best indication for clinical condition and prognostic evaluation were related mainly to the high level of CFS protein, it has also been reported in the literature , 19.The MRI and CSF laboratory parameters can be important tools for the clinician not only for diagnosis but also for having an estimate of the possible worsening of general conditions or the need to prepare measures to support life parameters.We believe it is important to establish how early the need for ventilatory support in the most severe patient is or to be able to decide to start physiotherapy in less severe cases. The need for this study also arises to give indications to the clinician in the sub-acute phase of the disease.Our study aimed to predict outcomes in GBS by the use of acute phase clinical features, laboratory analysis, and imaging. We have not found in the literature other studies that use laboratory, imaging, and clinical parameters to stage GBS together.On the other hand, our systematic search of the literature did not reveal studies that simultaneously evaluate the laboratory aspects of CSF and imaging and their relationship to the clinical conditions of children with GBS.Especially considering the ongoing International GBS Outcome Study, the potential association among CSF protein, imaging, and disability score may be worthy of further exploration .The study has several limitations in our opinion: the population has a heterogeneous age and this could vary the response to the disease of different patients. In the literature, the early age of onset is a negative prognostic factor . The samThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The study was conducted ethically in accordance with the World Medical Association Declaration of Helsinki and approved by the Ethics Committee of the University of Catania, Italy . Written informed consent was obtained from the parents.PP, FP, AF, and MR worked with and helped gather patient data. FG, TT, RR, AG, GC, and ADN drafted the present manuscript. AB, GB, and ADM were the radiologist consultant. PP, ET, MS, and AG were responsible for revising the work critically for important intellectual content. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.