Patients with a primary diagnosis of AR (ICD-9-CM code: 477.9) in 2010 were included, and the National Health Insurance Research Database in Taiwan was used as the data source. Association rule mining and social network analysis were used to establish and explore the CHM network. Possible molecular pathways of the CHM network were summarized and compared with commonly used western medicine (WM) by conducting overrepresentation analysis in the Reactome pathway database. The potential proteins acted by CHMs were obtained from the CHM ingredient-protein databases, including STITCH, TCMSP, TCMID, and TCM@Taiwan.  There were 89,148 AR subjects found in 2010, and a total of 33,507 patients ever used CHM. On an average, 5.6 types of CHMs were utilized per prescription. Xin-Yi-Qing-Fei-Tang was used most frequently , while Xiao-Qing-Long-Tang with Xin-Yi-San was the most commonly prescribed CHM-CHM combination. Up to six distinctive clusters could be found among the CHM network, and core CHMs could be found for AR, such as Xiao-Qing-Long-Tang and Xin-Yi-Qing-Fei-Tang. A total of 140 molecular pathways were covered by the CHM network , while 39 WMs covered 55 pathways. Among pathways responding to the immune system, WM mainly acted on cytokine signaling-related pathways, while CHM mostly acted on neutrophil/macrophage-related innate pathways and dendritic cell-related adaptive immunity pathways.  Our study demonstrated and analyzed the CHM network for AR. Core CHM for AR and possible molecular pathways were presented as well, and this information is crucial for researchers to select candidates for CHM-related studies. Allergic rhinitis (AR) is a significant global health problem affecting 10%–25% of the population and over 500 million patients worldwide . AR patiIn addition to western medicine (WM), the use of Chinese herbal medicine (CHM) is not uncommon, and the respiratory system and allergic diseases are both the primary reasons to use CHM , 14. ForFor this reason, it is vital to analyze the prescription patterns to find out the core part of CHMs for AR. Kung et al. reported the most commonly used single CHM and the CHM-CHM combinations by using Taiwan's clinical data in 2002 . AdditioThis study aims to demonstrate the CHM network, explore the core CHMs, and explore the possible pharmacology mechanisms' CHMs for AR by connecting the CHM network to biomedicine databases in the network pharmacology approach. Additionally, we also compared the proposed molecular pathways covered by the CHM network with all kinds of WMs for AR to assume the different roles of WM and CHM in treating AR. The results of this study would enhance the understating of CHM for AR for both WM and TCM researchers.The National Health Insurance Research Database (NHIRD), with high coverage (>99%) of medical records from all inhabitants enrolled in the National Health Insurance program in Taiwan since 1995, was used as the data source for this study. This database included comprehensive information about each patient's medical utilization and demographic features, such as in-patient and out-patient management, drop-off prescriptions, patients' gender, birth date, comorbidities, living space, medical expenditure, examinations, biochemical tests, reasons to visit/admission, and insured level. The NHIRD contains nearly all interventions made by qualified specialists, including WM, TCM doctors, and dentists, and therefore becomes an unequaled and suitable data source for observational studies , 26, 27.http://www.theplantlist.org/), and Chinese names in pinyin were used to present HFs, followed by lists of SHs. Additionally, all pharmaceutical factories must conform to the regulation of good manufacturing practice (GMP), which has been zero tolerance to heavy metal, pesticide, or even known toxins, such as aristolochic acid.Two types of CHMs were contained in the CHM prescription database: herbal formula (HF) and single herb (SH). Every SH was a kind of concentrated powder made from either part of natural plants, animals, minerals, and insects according to the preparation methods suggestions in TCM pharmacopeia. On the other hand, HF was a mixture of more than one kind of SH with fixed proportion according to the CHM classics, and the mixes were performed in the pharmaceutical factories before selling. In this study, pharmaceutical names were used to present SHs by searching the Plant List website (https://dep.mohw.gov.tw/DOCMAP/lp-874-108.html) . Also, the ingredients of every CHMs were retrieved from TCM pharmacopeia and three databases, including the Traditional Chinese Medicine Systems Pharmacology (TCMSP), TCM Database@Taiwan, and the Traditional Chinese Medicine Integrated Database (TCMID) [Furthermore, the composition of CHM preparations was acquired from the webpage provided by the Ministry of Health and Welfare in Taiwan, which has been the authority of the marketing and quality control of all CHMs ( (TCMID) –32. To sTwo parts of statistical analysis were performed. First, descriptive statistics were used for presenting baseline features of TCM users, such as age, gender, comorbidities, insured level, living locations, and coexisting WM and comorbidities, and these features were compared with CHM nonusers. Second, association rule mining (ARM) and social network analysis (SNA) were both used to construct the CHM network for AR. The data processing protocol was presented in our previous works about the CHM network for allergic skin diseases . In shorThe top 100 CHM-CHM combinations were further used to construct the CHM network and analyzed by SNA for every CHM role in the CHM network. By analyzing the relations of CHMs in the network, CHMs could be grouped into different clusters, in which CHM with closer relationships would be grouped , 34. MorFurthermore, CHM indications and possible molecular mechanisms were incorporated into the CHM network, and the mechanisms of WM were obtained to broaden the understanding of the CHM network from both TCM and WM viewpoints. The WM for AR were collected from the latest guideline and listed in the supplementary materials S3. CHM indications were obtained and summarized from CHM pharmacopeia . On the p value ≤0.05 represented significant results.The freeware KNIME (version 3.4) was used to deal with the databases, and NodeXL was used to build up the networks and perform SNA. The commercial statistical software STATA  was used to carry out the descriptive statistical analysis. Statistics with a p value <0.001). Although the causality was unable to be ensured due to the cross-sectional design of this study, we found that patients with allergic comorbidities such as atopic dermatitis  and chronic sinusitis  tended to use CHM. Most people used more than two kinds of WM , and this trend was more prominent among CHM nonusers .A total of 33,507 patients with AR were identified as CHM users, while 55,641 CHM nonusers were found . There wPlatycodon grandiflorum (Jacq.) A. DC. (19.1%) was the most prescribed SH of all prescriptions, followed by Glycyrrhiza uralensis Fisch. (16.5%), Angelica dahurica Benth. et Hood. F. (16.2%), Scutellaria baicalensis Georgi (15.8%), and Fritillaria thunbergii Miq. (15.5%) , and 6.3% of prescriptions contained at least ten kinds of CHMs . Among a (15.5%) . The preHouttuynia cordata Thunb. , Saposhnikovia divaricata (Turcz.) Schisch. combined with Schizonepeta tenuifolia (Benth.) Briq. , Glycyrrhiza uralensis Fisch. combined with Platycodon grandiflorum (Jacq.) A. DC. , and Platycodon grandiflorum (Jacq.) A. DC. combined with Fritillaria thunbergii Miq. .Furthermore, CHM-CHM combinations were explored to build up the CHM network, and the top 10 commonly used CHM-CHM combinations are listed in Angelica dahurica Benth. et Hood. F. Moreover, some CHMs were isolated from other clusters but formed strong connections between each other. For example, Forsythia suspensa (Thunb.) Vahl. and Lonicera japonica Thunb. composed cluster 5, and Cyperus rotundus L. and Jia-Wei-Xiao-Yao-San composed cluster 6.To explore the mixed pharmacological effects of the CHM network with consideration of CHM-CHM combinations and examine the differences in molecular mechanisms between CHM and WM, we investigated possible actions of CHMs and WMs by using the abovementioned methods. A total of 39 kinds of WMs and 31 kinds of CHMs  were used to find their target proteins. All WMs are listed in the supplemental material S3, and the compositions of HF preparation and ingredients are provided in the supplementary materials S1 and S2, respectively. Supplementary material S4 shows all possible binding proteins of every CHM and WM. Also, the potential molecular pathways of CHM clusters and WM were proposed by considering binding proteins within every cluster and seemed quite different . WMs maiAs external validation, we manually searched works of literature of CHMs in the network .In this study, we illustrated the CHM network to present core CHMs for AR and proposed the potential pharmacological mechanisms by utilizing freely accessible biomedicine databases to analyze the real-world clinical database. For treating AR, multiple CHMs used in one prescription are as common as our earlier reports about CHM network allergic skin diseases . This phThrough analyzing the CHM network, several implications could be explored: (1) the primary “TCM syndromes” that CHMs used to treat AR, (2) the different roles of CHM and WM on managing AR, (3) core CHM formula, and (4) unique CHM-CHM combinations. TCM syndrome could be a concise summary of disease, and recognition of TCM syndrome is vital to understand the principle of CHM treatments. By incorporating indications to CHMs, the preferable TCM syndrome for AR could be proposed. Wind-cold-dampness syndrome (cluster 2) and wind-heat syndrome (cluster 1) seemed the primary syndromes for CHM, and this trend is also observed in clinical trials , 61. TheIn addition to TCM syndrome, CHMs seemed to have special pharmacological effects as mutually complementary therapies to WM for AR. Overall, CHMs covered more molecular pathways when compared to commonly used WMs. The far larger number of identifiable pure compounds among CHMs may be the primary reason . Although most TCM doctors prescribe CHMs for AR based on TCM theory, rather than pharmacological mechanisms at the molecular level, the molecular pathways proposed by each CHM cluster uncover the reasons why these CHMs were chosen and rationales of CHM combinations. When focusing on immune system-related molecular pathways, the CHM clusters covered mainly pathways involved in the innate and adaptive immune systems; in contrast, WM mostly acted on cytokine signaling pathways, primarily interleukin-related actions . AccordiHouttuynia cordata Thunb. They shared similar mechanisms such as anti-inflammation and antibacterial effects. Xin-Yi-Qing-Fei-Tang can reduce the nasal colonization of Streptococcus pneumonia, which causes sinusitis and increases tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), and monocyte chemotactic protein-1 (MCP-1) levels and the migration of macrophages [Houttuynia cordata Thunb. shows antibacterial effects against methicillin-resistant Staphylococcus aureus (MRSA) and antibiofilm activity against MRSA and induced interleukin-8 (IL-8) [Although CHMs seemed to have some effects other than WMs, the exploration of core CHM for AR is still needed since CHM prescriptions are often too complicated to understand. Using SNA for the CHM network, we proposed core CHM for each cluster, with high degree centrality and prevalence. As for wind-heat syndrome (cluster 1), Xin-Yi-Qing-Fei-Tang was the core formula and strongly connected to rophages . Houttuy8 (IL-8) . MicrobiOn the other hand, for the wind-cold-dampness syndrome (cluster 2), Xiao-Qing-Long-Tang with the highest prevalence and degree centrality seemed to be the core formula. The interconnections between CHMs reflected the principle of composing CHM prescription, the so-called “sovereign, minister, assistant, and courier.” In this case, as the core formula, Xiao-Qing-Long-Tang dispels the wind-cold and dampness , and the effect can be strengthened by adding Xin-Yi-San as the “minister” part of the formula for patients with more cold-caused symptoms, such as nasal obstruction or rhinorrhea. Besides, the other CHMs in cluster 2 may serve as “assistant” and “courier,” which means optional CHMs to specific conditions, such as Xiang-Sha-Liu-Jun-Zi-Tang for patients with more dampness and Cang-Er-San for patients with possible heat transformation, which is similar to AR complicated with sinusitis. The principle of combing these CHMs is quite reasonable from the pharmacological viewpoint. Xiao-Qing-Long-Tang helps the body regulate T cell functions, and the immunomodulation on the adaptive immune system may be enhanced when combining Xiao-Qing-Long-Tang with Xin-Yi-San and Xiang-Sha-Liu-Jun-Zi-Tang , 71, 72.Forsythia suspensa (Thunb.) Vahl. and Lonicera japonica Thunb. were positively associated with each other but had no relations to other CHMs in the network. Both CHMs can clear heat and detoxify, and they were essential CHMs for treating allergic skin disease or acne due to their profound anti-inflammatory effects [Additionally, “drug pair” is a kind of unique CHM-CHM combination noted in the CHM network (clusters 5 and 6 in  effects , 21, 73.Centipeda minima [α were the common target proteins. However, from the CHM network perspective, the influence on the immune system would be more extensive when combing certain CHMs. By referencing to Reactome database, more detailed molecular pathways could be found in both adaptive and innate immune systems.There were some similarities and differences between this study and previous studies about CHM prescriptions for AR. Kung et al. and Lin et al. reported the common single CHM and CHM-CHM combinations for AR in Taiwan with different time frames in our study , 20. Thea minima . OverallUsing the real-world data and CHM network analysis, we can graphically demonstrate the CHM prescriptions for AR, and we first connect the freely accessible biomedicine databases and CHM network to the proposed potential effects of CHM freely. Relying on the nature of the NHIRD, the high coverage of Taiwan inhabitants, and well-established electronic medical records, selection bias and recall bias could be minimized, and these results could be regarded as a sort of consensus summarized from real-world clinical data. However, there are still some drawbacks to this study. First, since the CHM prescriptions are obtained from the Taiwan clinical database, the generalizability would be a problem since the differences in environments or patients' constitution may influence the CHM prescribed for AR patients. Nevertheless, we provided a possible way to connect clinical data to biomedical databases, and the effects of CHMs on AR would be more exact if more studies from other places are conducted in the future. Second, there were no data about TCM syndrome or AR symptoms recorded in this database. Although we can propose preferable TCM syndrome by analyzing the CHM network, comprehensive data collection about TCM syndrome is still needed . The resWe graphically demonstrated the CHM network for AR in this study, and by connecting the CHM network to the biomedicine database and comparing the possible molecular pathways of CHM with WM, the complementary roles of CHM and WM are proposed as well. The results would broaden the horizon on using CHM and WM for AR, and it would become an essential reference for further clinical studies and experiments.


The token exchange paradigm shows that monkeys and great apes are able to use objects as symbolic tools to request specific food rewards. Such studies provide insights into the cognitive underpinnings of economic behaviour in non-human primates. However, the ecological validity of these laboratory-based experimental situations tends to be limited. Our field research aims to address the need for a more ecologically valid primate model of trading systems in humans. Around the Uluwatu Temple in Bali, Indonesia, a large free-ranging population of long-tailed macaques spontaneously and routinely engage in token-mediated bartering interactions with humans. These interactions occur in two phases: after stealing inedible and more or less valuable objects from humans, the macaques appear to use them as tokens, by returning them to humans in exchange for food. Our field observational and experimental data showed (i) age differences in robbing/bartering success, indicative of experiential learning, and (ii) clear behavioural associations between value-based token possession and quantity or quality of food rewards rejected and accepted by subadult and adult monkeys, suggestive of robbing/bartering payoff maximization and economic decision-making. This population-specific, prevalent, cross-generational, learned and socially influenced practice may be the first example of a culturally maintained token economy in free-ranging animals.This article is part of the theme issue ‘Existence and prevalence of economic behaviours among non-human primates'. Like a symbolic tool, a token is an inherently non-valuable (e.g. inedible or non-nutritive) object that acts as a secondary conditioned reinforcer; indeed, it only acquires an instrumental or functional value through the arbitrary associations made with the goods (e.g. food) or services  it is conventionally exchanged for in a barter-like situation, even though the object bears no iconic relation to its referent ,2. The tHowever, most of these experimental procedures involve human-induced exchanges with relatively small samples of individually trained, laboratory-bred subjects. During the experiments, these subjects (i) are typically placed in isolation from their conspecifics and their other daily activities, (ii) exchanged in constrained environments characterized by a lack of alternative response options, and (iii) received small rewards for the correct actions  spontaneously and routinely engage in token-mediated bartering interactions with humans. These interactions occur in two phases: after stealing inedible and more or less valuable objects  from temple visitors, the macaques appear to use them as tokens, by returning them to humans in exchange for a certain number/type of food rewards proffered by the temple staff [spontaneous expression of token-mediated bartering interactions in naturalistic circumstances (i.e. the macaques initiate token-robbing interactions without any encouragement from humans). These interactions are at least partially monkey-driven , and exhibited by a large number of free-ranging individuals [Around the Uluwatu Temple in Bali, Indonesia, a large free-ranging population of long-tailed macaques  population-specific, because it was not observed in other anthropogenically influenced populations of Balinese macaques where it would be ecologically possible, (ii) frequent (7.8 robbing events/hour and 3.3 bartering events/hour), (iii) prevalent (49.3% of identified population members performed robbing behaviour and 35.6% performed both robbing and bartering behaviours), (iv) performed by individuals from all age/sex classes in the five neighbouring social groups of this population, (v) characterized by substantial intrapopulational intergroup variation in its frequency and prevalence (but not success), which was explained by anthropogenic influences , and to a lesser extent, demographic correlates adult males, but not group density), (vi) a behavioural candidate for the process of ‘cultural zones'  via intergroup observational learning or intergroup transfers of male group members, (vii) socially influenced and synchronized in its group-level expression, following a behavioural contagion-like effect, owing to response facilitation and possibly conformity-biased learning, (viii) not influenced by model-based biases , and (ix) an established practice in this population, probably passed on cross-generationally for at least 30 years, though detailed information on its origins is lacking ,16. HowePrediction 1a), (ii) an increase in token/reward-bartering success , and (iii) more negotiated successful token/reward-bartering sequences  previously rejected; Prediction 1c).This study aimed to fill this knowledge gap by testing three hypotheses pertaining to the acquisition and skillful performance of robbing and bartering interactions in the Uluwatu population of long-tailed macaques. First, the ‘experiential learning' hypothesis posits age differences in robbing/bartering success. Indeed, each of the two aforementioned phases (i.e. robbing and bartering) comprises several successive behavioural steps or strategies that must all be appropriately completed by the monkey for the phase to be considered successful. Both token-robbing and token/reward-bartering are challenging tasks for a monkey and require specific perceptual learning, sensorimotor coordination and cognitive skills. From juveniles to subadults to adults, we predicted (i) an increase in token-robbing success . When two tokens of different values were available on a given temple visitor, we predicted that subadult and adult monkeys would preferentially select the higher-valued token, whereas no significant difference was expected in juvenile monkeys (Prediction 2b). We predicted a similar age difference in the value-based token selection during field experiments, after controlling for token accessibility and lateral bias (Prediction 2c).Second, assuming a hierarchical scale of values attributed by humans to different tokens , the ‘value-based token selection' hypothesis posits age differences in the selection of higher-valued tokens by the monkeys during the token-robbing phase. From juveniles to subadults to adults, we predicted an increase in the relative selection of higher-valued tokens available among Prediction 3a), and (ii) accumulate more than one of the proposed food rewards (Prediction 3b) before returning the token when it is a higher-valued token. In terms of reward quality, they should (i) reject more low-preferred food rewards before returning the token when it is a higher-valued token (Prediction 3c) and (ii) more likely end a successful token/reward-bartering sequence by returning the token in exchange for a type of food reward different from the one(s) previously rejected when it is a higher-valued token (Prediction 3d). Conversely, subadult and adult subjects should more likely end a successful token/reward-bartering sequence by returning the token in exchange for a low-preferred food reward when it is a lower-valued token (Prediction 3e).Third, assuming that economic decision-making requires cognitive maturity, the ‘robbing/bartering payoff maximization' hypothesis posits clear behavioural associations between value-based token possession and quantity or quality of food rewards rejected and accepted by subadult and adult monkeys  during the token/reward-bartering phase. In other words, these individuals should respond differently to different token values, and use the token/reward-bartering phase to obtain either more food rewards or a more preferred food reward when they selected a higher-valued token. In terms of reward quantity, subadult and adult subjects should (i) wait to be proposed more food rewards (2.(a). The Uluwatu macaques were provisioned daily with a variety of fruits and vegetables provided by the temple staff, and fully habituated to human presence. Overall, this habitat is a human-dominated area characterized by highly frequent interactions with  people and a very low predation pressure [The Uluwatu Temple, located in a dry agricultural landscape of southern Bali, Indonesia, is a Hindu temple complex used by Balinese communities for daily religious ceremonies. It is also one of the most famous touristic spots on the island, visited by 1.5 million tourists in 2015 . A populpressure .(b)Observational data were based on the spontaneous expression of token-robbing and token/reward-bartering interactions between monkeys and humans, with no intervention from the researchers. These data were collected by using the combined ‘behaviour-dependent sampling' rule and the ‘continuous recording' rule . BehavioC) for monkey identities  and age–sex class identification , and distances in metres  [For each robbing/bartering event, one of the two observers video-recorded the complete token-robbing attempt and token/reward-bartering attempt, including the identity of the monkey being involved, the object (i.e. prospective token) being selected by the monkey, the number and type of other potential tokens directly accessible to the monkey (i.e. held or carried around by the human target), and the number and type of food reward(s) being (i) proposed/tossed to the monkey by an accustomed temple staff member typically located within 3 metres, (ii) ignored/rejected by the monkey with a ‘turning down' hand/arm gesture, and (iii) accepted/accumulated by the monkey by grabbing/cuddling the food reward(s). Because the monkeys were highly habituated to humans, most video-recordings were collected at close range (2–5 m) without disturbing the animals. Data collection started when the two observers reached high inter-observer reliability, as measured by the index of concordance ( = 0.91) ,19.absolute behavioural frequencies (i.e. number of events/behaviours per observation time unit) because the study site was too large for all robbing/bartering occurrences to be recorded at any time. However, this data collection method allowed us to quantify all the other variables used in this study  being available on, and selected from, a human target; individual average numbers of food rewards being proposed, rejected, and accepted) because these measures were based on the relative behavioural frequencies calculated from a total of recorded events. All these variables were obtained from video-scoring. This task was conducted by N.G., who transcribed all the video-recorded robbing/bartering interactions onto an Excel spreadsheet, with each aforementioned variable being coded to the second. To measure intra-coder reliability, N.G. transcribed twice a total of 6.2 h of video-recordings, involving 158 token-robbing attempts and 66 token/reward-bartering attempts, which represents 3% of the total numbers of token-robbing attempts and token/reward-bartering attempts included in the analyses of token-robbing success and token/reward-bartering success, respectively. The comparison of the two transcriptions for all the other variables analyzed in this study yielded a high score of coder consistency .(c)We used individual percentages of successful token-robbing attempts and successful token/reward-bartering attempts as valid measures of experiential learning by conducting cross-sectional analyses based on age differences. To calculate these percentages, we used each monkey subject as its own control by distinguishing for each attempt two possible outcomes—successful or unsuccessful—out of the total number of attempts for each subject.There was a four-stepped sequence of appropriate behaviours and environmental conditions leading to a successful token-robbing outcome: the monkey (i) stared at a prospective human target, (ii) inconspicuously approached the human target within 5 m, (iii) snatched the object from the human target (monkey–human body contact may or may not occur), and (iv) stepped aside while gripping the token. If any of these behavioural steps was not appropriately completed by the monkey, the token-robbing attempt was considered unsuccessful. To be included in the analyses of token-robbing outcome, an individual had to be involved in at least four token-robbing attempts . We believe that this minimum number of four attempts per individual made the distinction between unsuccessful and successful outcomes valid, while allowing us to reach a sample size for the ‘juvenile' age class that was conducive to statistical analysis.Following a successful token-robbing attempt, there was a three-stepped sequence of appropriate behaviours and environmental conditions leading to a successful token/reward-bartering outcome: the monkey (i) held onto the stolen object and remained present in the area for a potential token/reward-bartering attempt involving a human barterer , instead of fleeing with an object that only acquires a value for the monkey during the bartering process, (ii) engaged in a token/reward-bartering interaction, which may involve accumulating several food rewards before returning the token, or even discarding a (a number of) less preferred food reward(s) in anticipation of receiving a (number of) more preferred food reward(s), and (iii) refrained itself from damaging the token and returned it in good condition, because if the token was damaged by the monkey, the bartering interaction may not occur or may be interrupted. If any of these behavioural steps was not appropriately completed by the monkey, the token/reward-bartering attempt was considered unsuccessful. To be included in the analyses of token/reward-bartering success, an individual had to be involved in at least four token/reward-bartering attempts .(d)Nmissed = 260, Ntaken = 287); (ii) accessories ; (iii) hats ; (iv) shoes ; (v) pairs of glasses ; and (vi) electronic devices/wallets . Edible objects selected by the monkeys were not considered as tokens in our analyses.Our observational data showed six types of tokens selected  by the Uluwatu monkeys: (i) empty containers . Our observational data showed three groups (each containing two types) of value-based tokens on the basis of how often humans wanted to engage in token/reward-bartering interactions with the monkeys: (i) low-valued tokens, seldom bartered by humans: empty containers and accessories ; (ii) medium-valued tokens, often bartered by humans: hats and shoes ; and (iii) high-valued tokens, almost always bartered by humans: pairs of glasses and electronic devices/wallets .N = 1084, distributed across the six types of tokens as follows: (i) 127 empty containers; (ii) 107 accessories; (iii) 132 hats; (iv) 466 (pairs of) shoes; (v) 120 pairs of glasses; and (vi) 132 electronic devices/wallets. To assess the relative ease with which the six different types of tokens were stolen by the monkeys from human targets, we calculated, for each type of token, the average percentage of successful token-robbing attempts among all the subadult and adult monkeys (i.e. the most skilled robbers) that had each been involved in at least four token-robbing attempts targeting a given type of token in our observational dataset.To assess the relative local availability in the six different types of tokens, we examined a sample of 84 video-recorded token-robbing events, randomly selected from our observational data, that featured 500 potential human targets. For each of these potential human targets, we scored the number and the type of potential tokens directly accessible to the monkeys. From this representative sample, the total number of available tokens we obtained was Experimental data were obtained from value-based token selection tests administered to a subset of 15 monkeys belonging to the three age classes  by three experimenters between September and December 2019. When each of these subjects was not surrounded by other monkeys, it was presented with a binary choice between a medium-valued token and a high-valued token, each proffered at opposing sides of a black plastic tray (30 cm × 20 cm × 4 cm). The tray was placed on the ground at 1.2 m from the tested monkey. The preferentially selected token was deemed to be the one the subject (first) grasped/took possession of. Each subject was tested across 16 trials comprising four randomly rotated sessions of four randomly rotated binary choices between a medium-valued token and a high-valued token . To control for lateral biases in grasping behaviour, token orientation (i.e. left/right) was balanced across trials. To control for experimenter biases, the experimenters fixed their gaze at a fixed point away from the proffered tokens during each trial. Most of these trials were followed by token/reward-bartering attempts by experimenters to retrieve the tokens. In terms of timing, and as much as possible considering field study constraints, the trials were homogeneously distributed within and across subjects, with no more than five trials being performed on a given subject within a day. Experimental data collection started when the three experimenters reached 100% of concordance for monkey identities.(e)For analyses on food rewards rejected and accepted by the monkeys during the token/reward-bartering phase, we only considered the food items that the monkey could reach/grab when proposed/tossed to them by the human barterers. To assess individual preferences across the three types of proposed food rewards , we used our observational data on spontaneously expressed token/reward-bartering interactions.X was defined as the total number of times a certain reward type was the last one accepted by the monkey before returning the token and Y was defined as the total number of times this reward type was rejected by the monkey during token/reward-bartering sequences. The individual ‘likeability' score for a reward type was obtained by dividing X by (X + Y). The least-preferred type of food rewards for a given monkey was considered to be the one with the lowest ‘likeability' score.For a given monkey, we calculated three ‘food reward likeability' scores, one for each of the three types of proposed food rewards. When the three reward types were proposed during a token/reward-bartering sequence, we used two values: (f)H-tests followed, when significant, by post hoc Mann–Whitney U-tests. To test whether the monkeys selected the six different types of tokens based on their relative local availability, we used a Spearman rank-order correlation test between the numbers of the six types of tokens available from our sample of 500 potential human targets and the numbers of the six types of tokens selected by the monkeys within our entire set of observational data (i.e. the sum of Nmissed and Ntaken for each type of token). To test whether the monkeys preferentially selected tokens that were easier to steal from humans, we used a Spearman rank-order correlation test between the percentage of types of tokens selected and the average percentage of successful token-robbing attempts among subadult and adult monkeys. To test within-individual preferential selection of low-valued, medium-valued and high-valued tokens, we used Friedman tests followed, when significant, by post hoc Wilcoxon signed-rank tests. To test within-individual preferential selection between two tokens of different values available on a given human target, we used Wilcoxon signed-rank tests. Value-based token selection tests of binary choices between a medium-valued token and a high-valued token were analyzed by using binomial tests with a test proportion = 0.50. Because all our predictions were directional, we conducted one-tailed tests. Statistical analyses were performed using the IBM-SPSS Statistics-26 analytical program. Significance levels were set at α = 0.05.Because all our raw and  transformed data violated parametric assumptions, we conducted nonparametric tests. To test age differences in the percentage of successful token-robbing attempts, the percentage of successful token/reward-bartering attempts, and the average number of food rewards being proposed and rejected by the monkey, we used Kruskal–Wallis 3.(a)N = 376 attempts), 61.5% (N = 1829 attempts) and 68.8% (N = 3062 attempts) in juveniles, subadults, and adults, respectively. We found a statistically significant age difference in the percentage of successful token-robbing attempts . Post hoc pairwise comparisons revealed that subadults were more successful than juveniles , adults were more successful than juveniles , and adults were more successful than subadults , 89.4% (N = 689 attempts) and 92.0% (N = 1446 attempts) in juveniles, subadults and adults, respectively. We found a statistically significant age difference in the percentage of successful token/reward-bartering attempts . Post hoc pairwise comparisons revealed that subadults were more successful than juveniles  and adults were more successful than juveniles . However, adults and subadults did not significantly differ in percentages of successful token/reward-bartering attempts , the average number of food rewards being rejected by the monkey  and the average number of food rewards being rejected by the monkey before accepting a different type of food reward to end the token/reward-bartering sequence . In each of these three variables, subadults scored significantly higher than juveniles  and adults scored higher than juveniles . However, adults and subadults did not significantly differ in these scores . Even though we did not find a significant increase in the scores indicating negotiated successful token/reward-bartering sequences from juveniles to subadults to adults, Prediction 1c was partly supported owing to the difference between the former and the latter two age classes.During successful token/reward-bartering sequences, we found statistically significant age differences in the average number of food rewards being proposed to the monkey ((b)N = 6, sR = −0.17, p = 0.742). Moreover, the average percentage of successful token-robbing attempts among all the subadult and adult monkeys (i.e. the most skilled robbers) and the percentage of types of tokens selected from human targets were not statistically correlated .In the observational data, the relative local availability in the six types of tokens and the numbers of the six types of tokens selected by the monkeys within our entire set of observational data were not statistically correlated . However, we found statistically significant differences in the selection of the three differentially valued tokens by subadults  and adults . Post hoc pairwise comparisons revealed that subadults and adults preferentially selected high-valued over low-valued tokens  and medium-valued over low-valued tokens . There was no significant difference in the selection of high-valued or medium-valued tokens in subadults  and adults . Even though we did not find a significant increase in the relative selection of higher-valued tokens among all the prospective human targets from juveniles to subadults to adults, Prediction 2a was partly supported owing to the difference between the former and the latter two age classes.In the observational data, the percentages of selection of low-valued, medium-valued and high-valued tokens were, respectively, 25.3, 47.9 and 26.8% in juveniles, 18.8, 38.9 and 42.3% in subadults and 17.2, 41.4 and 41.4% in adults. We did not find any statistically significant difference in the selection of the three differentially valued tokens by juveniles , whereas no significant difference was found in juvenile individuals . Therefore, Prediction 2b was supported.However, when two tokens of different values were available on a given human target, we found that subadult and adult monkeys preferentially selected the higher-valued token , whereas no significant difference was found in juvenile subjects . Therefore, Prediction 2c was supported.In the experimental data, when two tokens of different values were available on plastic trays placed in front of a tested monkey, we found that subadult and adult subjects preferentially selected the higher-valued token Nsubadult = 12, z = −3.1, p = 0.002; Nadult = 40, z = −3.0, p = 0.003). Low-valued tokens could not be used in these analyses because, by definition, they were typically not bartered by the temple staff. Still, Prediction 3a was supported.In this section about economic decision-making , we focused on the most skilful and selective individuals during the token/reward-bartering phase, namely, subadult and adult monkeys. In terms of reward quantity, subadult and adult subjects waited to be proposed more food rewards before returning the token when it was a higher-valued token  and adult subjects . Therefore, Prediction 3b was supported.We also found that the percentage of successful token/reward-bartering sequences when more than one of the proposed food rewards were accumulated by the monkey before returning the token was significantly higher when the monkey was holding a high-valued token than when it was holding a medium-valued token, both in subadult . However, this difference was not statistically significant in subadult subjects . Therefore, Prediction 3c was supported for adult, but not for subadult subjects.In terms of reward quality, and as expected, the average percentage of rejections, by adult subjects, of the least-preferred type of food rewards (when at least one reward among the least-preferred type was proposed during a given token/reward-bartering sequence) was significantly higher when they were holding a high-valued token, compared to a medium-valued token  or in adults . Therefore, Prediction 3d was not supported.Contrary to our expectations, there was no significant difference in the average number of food rewards being rejected by the monkey before accepting a different type of food reward to end the token/reward-bartering sequence when it was holding a high-valued token, compared to a medium-valued token, either in subadults . Therefore, Prediction 3e was supported.Finally, subadult and adult subjects were significantly more likely to end a successful token/reward-bartering sequence by returning the token in exchange for the least-preferred type of food rewards (provided at least one reward among the least-preferred type was proposed during a given token/reward-bartering sequence) when they were holding a medium-valued token compared to when they were holding a high-valued token  these behaviours need to be learned throughout juvenescence (i.e. until up to 4 years in this species) to be successfully performed; (ii) older monkeys preferentially selected tokens that were more valued by humans; and (iii) these more skilful and selective individuals appeared to make economic decisions, as evidenced by clear behavioural associations between value-based token possession and quantity or quality of food rewards rejected and accepted.(a)As predicted, we found a significant increase in token-robbing success from juveniles to subadults to adults, whereas the main behaviour patterns required for the successful performance of token/reward-bartering interactions were already in place from around 4 years (i.e. in subadults). Likewise, the ability to engage in more negotiated successful token/reward-bartering sequences—during which the monkey only returned the token after being proposed more food rewards, or after rejecting more food rewards, or after accepting a type of food reward different from the one(s) previously rejected—was not fully acquired before the subadult stage.These results lend some support to the ‘experiential learning' hypothesis, whereby token-robbing and token/reward-bartering interactions are multi-stepped and complex behavioural sequences requiring perceptual learning, sensorimotor coordination and cognitive skills  to be successfully performed; they are thus gradually acquired through extended individual practice during the juvenile period, in part via experiential trial-and-error learning. It is noteworthy to mention that the development of (sub)adult-level proficiency at robbing/bartering is not only dependent on skill learning , but may also be constrained by physical maturation. This is particularly true during the token-robbing phase that often involves monkey–human body contact and/or requires muscular strength when a monkey has to yank on a flip-flop still worn by an adult human. In these cases, the limited physical capabilities of juveniles, and the maturing bodies of subadults, may partly explain the significant increase in token-robbing success from juveniles to subadults to adults.Primates are characterized by the longest juvenile period in relation to life span of all mammals . Accordi(b)The first step in economic decision-making requires the cognitive ability to distinguish among different expected material values of a given symbolic currency . After showing that token selection was not significantly affected by token availability and the relative ease with which different types of tokens were stolen by the monkeys from human targets, our observational data revealed a marked age difference in how the monkeys responded to a human-based three-level hierarchy of valuable objects. When considering the token selection among all the prospective human targets , juveniles did not show any preferential selection among low-valued, medium-valued and high-valued tokens, whereas subadults and adults preferentially selected high- and medium-valued tokens over low-valued ones. When two tokens of different values were available on a given human target, subadults and adults preferentially selected the higher-value token, whereas juvenile individuals did not show any significant difference. We found a similar age difference in the value-based token selection, after experimentally controlling for token accessibility and lateral bias.These results support the ‘value-based token selection' hypothesis, positing age differences in the selection of higher-valued tokens by the monkeys during the token-robbing phase that are indicative of a developmental trajectory toward more strategic choices in more mature individuals. Subadult and adult monkeys (but not juveniles yet) have learned to map their token-robbing behaviours onto the hierarchical (and arbitrary) scale of values attributed by humans to different tokens: they preferentially selected tokens that were more likely to be exchanged for food  over other objects that were less valuable for humans and typically not worth bartering . Our findings are consistent with data obtained in other non-human primate species, showing that subadult and adult capuchin monkeys and chimpanzees correctly preferred a high-valued token over a low-valued token in an experimental bartering situation ,11,23.(c)The second step in economic decision-making requires the cognitive ability  to respond differently to differentially valued tokens by trying to maximize one's payoff. We found evidence for such behavioural associations between value-based token possession and quantity or quality of food rewards rejected and accepted by subadult and adult monkeys  during the token/reward-bartering phase. They consistently and actively obtained either more food rewards or a more preferred food reward in exchange for a higher-valued token. They were also more likely to end a successful bartering interaction by accepting a less preferred food reward in exchange for a lower-valued token.Our findings support the ‘robbing/bartering payoff maximization' hypothesis in that subadult and adult monkeys strategically responded to differentially valued tokens in their possession by adjusting the amount or type of food rewards they gained from the barters. The result showing that subadults (unlike adults) failed to significantly reject more low-preferred food rewards before returning a higher-valued token may be explained in terms of poorer temporal cognition or higher impulsivity (compared to adults): subadult long-tailed macaques may either not have yet acquired the cognitive capacity to anticipate the subsequent proffering of more preferred food rewards in this specific situation, or not be patient/self-controlled enough to wait for possibly more preferred food rewards.Overall, our field observational data are in line with laboratory-based studies showing that several non-human primate species can (i) understand the effectiveness of tokens as secondary reinforcements to make simple calculations about quantities of reward, (ii) determine an item's value on the basis of its perceived utility (e.g. exchanging only a low-preferred reward for a tool necessary to reach a more preferred reward) and (iii) recognize the appropriate conditions in which a successful exchange could occur  ,2,23–27.5.Token-robbing and token/reward-bartering are cognitively challenging tasks for the Uluwatu macaques that revealed unprecedented economic decision-making processes  in a large monkey population living in an anthropogenically impacted habitat. This spontaneous, population-specific, prevalent, cross-generational, learned and socially influenced practice may be the first example of a culturally maintained token economy in free-ranging animals. The present naturalistic research setting represents a unique opportunity to study field economics and explore macroeconomic phenomena in non-human primates in environmental conditions that are more externally and ecologically valid than those provided by the traditional token exchange paradigm. Further experimental research on the Uluwatu macaques should make future cross-species comparisons of economic decision-making and symbolic tool use more relevant from an evolutionary perspective and may ultimately lead to a better understanding of the origins of autonomous monetary systems in humans .


Three drug combinations, ipilimumab-nivolumab (Ipi-Nivo), pembrolizumab-axitinib (Pembro-Axi), and avelumab-axitinib (Ave-Axi), have received regulatory approval in the USA and Europe for the treatment of metastatic renal cell carcinoma with clear cell component (mRCC). However, no head-to-head comparison data are available to identify the best option. Therefore, we aimed to compare these new treatments in a first-line setting. We conducted a systematic search in PubMed, the Cochrane Library, and clinicaltrials.gov for any randomized controlled trials of treatment-naïve patients with mRCC, from January 2015 to October 2019. The process was performed according to PRISMA guidelines. We performed a Bayesian network meta-analysis with two different approaches, a contrast-based model comparing HRs and ORs between studies and arm-based using parametric modeling. The outcomes for the analysis were overall survival, progression-free survival (PFS), and objective response rate. Our search identified 3 published phase 3 randomized clinical trials (2835 patients). In the contrast-based model, Ave-Axi (SUCRA = 83%) and Pembro-Axi (SUCRA = 80%) exhibited the best ranking probabilities for PFS. For overall survival (OS), Pembro-Axi (SUCRA = 96%) was the most preferable option against Ave-Axi and Ipi-Nivo. Objective response rate analysis showed Ave-Axi as the best (SUCRA: 94%) and Pembro-Axi as the second best option. In the parametric models, the risk of progression was comparable for Ave-Axi and Ipi-Nivo, whereas Pembro-Axi exhibited a lower risk during the first 6 months of treatment and a higher risk afterwards. Furthermore, Pembro-Axi exhibited a net advantage in terms of OS over the two other regimens, while Ave-Axi was the least preferable option. Overall evidence suggests that pembrolizumab plus axitinib seems to have a slight advantage over the other two combinations. Over the past few years, the treatment for metastatic renal cell carcinoma with clear cell component (mRCC) has drastically changed with the introduction of targeted therapy, immunotherapy, and a better understanding of RCC biology ,2,3,4. SThe shift in systemic therapy of mRCC has just begun, and phase 3 results with these new available combinations raise many questions that need to be addressed in order to make better use of them in clinical practice. In addition, we still lack predictive biomarkers and prognostic characteristics in patients or the disease to guide treatment allocation. Results of these phase 3 trials should be interpreted in the context of the International Metastatic RCC Database Consortium (IMDC) risk classification, which has proven its utility since the targeted therapy era ,13.Comparison between these therapeutic options is one of the main concerns for clinicians and patients . HoweverWe specifically focused on randomized controlled trials (RCTs), including naïve-treatment patients with mRCC with clear cell component who received one of the combinations involving ICIs in the first-line setting, with no patient restrictions on PD-L1 or the IMDC subgroup. The study was conducted based on PRISMA extended guidelines for network meta-analysis . We perfThe whole process of trial selection, full-text screening, and data extraction was performed by two investigators  independently; if disagreement occurred, it was resolved by discussion with other investigators. For all selected studies, risk of bias was assessed with the Cochrane Handbook tool .We used two different approaches: a contrast-based method comparing the relative treatment effect in the intention-to-treat population as well as in the IMDC subgroups, and an arm-based method using Kaplan–Meier curves to estimate the parametric survival model (in the ITT population only). We performed both fixed-effect and random-effect models for the contrast-based approach. To assess which treatment was likely to be the best option, we used rank probabilities and the surface under the cumulative ranking curve (SUCRA)  in the cThis approach focused on relative effects using HR on a log scale to run an NMA model as described in Dias 2013 .To circumvent the apparent violation of the proportional hazard assumption of the Cox model in the published PFS Kaplan–Meier curves of the CheckMate 214 study ,20.Statistical analyses were all performed within a Bayesian framework. Credible intervals were all reported at the 95% level. The contrast-based analysis was performed using R (version 3∙6∙0)  and JAGS (version 4∙3∙0) with the package “getmtc” (version 0∙8∙2)  and OpenThere was no funding source for this study. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.Our search identified 72 results. Of these, three published phase 3 randomized clinical trials matched our selection criteria ). However, the Ipi-Nivo combination was less efficient (HR: 0.81 (0.57–1.20)) compared to Ave-Axi or Pembro-Axi (HR: 0.82 (0.58–1.20)). Ranking suggested Ave-Axi as the best option (SUCRA = 83%) and Pembro-Axi as the second best (SUCRA = 80%), but the difference was not clinically relevant . For OS,Fixed-effect and random-effect models yielded similar results, with larger credibility intervals for the random-effect model . SensitiThe IMDC subgroup analysis was performed for PFS and ORR only, since OS data were immature with many censored patients from the Javelin Renal 101 trial. We pooled the intermediate and poor IMDC risk subgroups to match the CheckMate 214 results with the other trials. Patient proportion in each subgroup is reported in Among the different models tested, a Weibull model offered the best compromise between fit and complexity.The time-dependent HR of the drug combinations vs. sunitinib clearly suggest a violation of the main assumption of proportional hazards in the three trials, primarily for OS, and especially in the CheckMate 214 trial for both OS and PFS A. Risk oThe aim of this study was to provide an indirect comparison between the three combinations. We allowed sunitinib’s effect to be different across each study instead of arbitrarily taking a mean effect, accounting for the variability of sunitinib’s effect, as observed in the different control arms. Benefit was in favor of Pembro-Axi over Ave-Axi and Ipi-Nivo during the first 5–7 months of treatment, which reversed afterwards. Ipi-Nivo and Ave-Axi displayed a comparable benefit with a higher risk of progression for Ipi-Nivo at the beginning of the treatment period, as in The time-dependent HR curves for OS suggested that all three drug combinations have comparable time effects on OS A. We alsThe main observations resulting from the indirect pairwise comparison of the three combinations suggested a higher risk of death with Ipi-Nivo compared to Pembro-Axi throughout the study period B. The hiUpon indirect comparison, there was no significant difference between the trials, suggesting that these patients may respond well to all combinations , with alThe three combinations considered in this study may soon become new standards of care in the first-line setting for mRCC, without any clear rationale to prefer one over the other. We aimed to fill this knowledge gap by conducting indirect comparisons, and thus hopefully providing clinicians with critical aid in decision-making.Network meta-analysis is a powerful and flexible method of comparing multiple different therapeutic strategies. To our knowledge, few NMAs have been published in an mRCC first-line setting. Andrew W. Hahn et al. concluded that cabozantinib, Pembro-Axi, and Ave-Axi were preferable for PFS, and Pembro-Axi appeared superior for OS in first-line mRCC . HoweverHowever, our approach significantly differed from these studies: we specifically focused our comparison on the efficacies of the three combinations with immune checkpoint inhibitors that have demonstrated a benefit in phase 3 trials . We used the most recent data (up to August 2019) and employed both fixed- and random-effect models. Moreover, we used two different approaches to assess these different therapeutic options: a contrast-based and an arm-based approach. In our arm-based approach, we relaxed the assumption of a common effect of sunitinib to best model the actual trial differences. We also investigated models that may have taken into account various confounding factors, such as the between-study unbalanced prognostic risk groups, in order to allow for sufficient flexibility in the modelling of these new combinations complexities . In our study, we compared three large multicenter phase 3 randomized controlled trials which included 2843 patients in total. In the contrast-based approach, Pembro-Axi was found to be the best option for the OS rate in the ITT population, whereas Pembro-Axi and Ave-Axi showed comparable efficacy for PFS, and Ave-Axi showed the best ORR efficacy. On the other hand, in the IMDC favorable risk group, Ave-Axi showed the most favorable results for PFS. Contrast-based approaches for both PFS and OS led to results close to what was reported in each independent updated study, due to the fact that only one study was available for each comparison and that we decided upon non-informative priors for treatment effects . In the arm-based approach (in the ITT population), Pembro-Axi seemed to be the preferable option only for the OS. We also observed that during the first 5 months of therapy, IO-TKI (immunotherapy and TKI) combinations exhibited a lower risk of progression compared with IO-IO combinations; however, Ipi-Nivo exhibited longer PFS in patients who did not progress during the first 5 months. This may be partially related to pseudo progression induced by the double IO combination, while having a high rate of complete response for the remaining patients in the CheckMate 214 trial.Our study has both strengths and limitations. First, we focused on the new promising regimens, with results from published phase 3 randomized clinical trials, in order not to inflate population and design heterogeneity. Second, we used two different but complementary approaches for more consistent results: the contrast-based approach, which uses HRs as relative treatment effects and maintains the randomization structure within each study but requires strong assumptions. An arm-based approach is more likely to relax these assumptions, but the disadvantage is that it does not preserve the randomization structure. Moreover, in the contrast-based approach, HRs derived from the Cox model rely on the assumption of proportional hazards, which is commonly violated in many trials, leading to biased estimates. Arm-based methods do not rely on HR but need the parametric fit of Kaplan–Meier (KM) curves. Third, combinations may have more complex mechanisms of action than monotherapies, and to this end arm-based methods provide time-dependent HR, interpretations of which may help to decipher such mechanisms better than constant HR and decide which combination may be the best and when. One main limitation is the overall lack of data, which may reflect a potential uncontrolled bias; more studies comparing these regimens and/or individual patient data would be needed in order to improve the precision and heterogeneity of estimations. These additional data would also allow us to test for inconsistency (confirm concordance between direct and indirect comparisons), which was not possible in our current star-shaped network. IMDC subgroups and geographic regions may represent other confounding factors across comparisons; more studies are needed to adjust the NMA model and confirm our findings. We tried more complex multivariate NMAs to account for HRs per IMDC subgroup in one single model, but a lack of data for OS in each risk group prevented us from refining the final model. It could also have been relevant to consider PD-L1 expression, which may have differently influenced the PFS of the combinations, but given the different assays and thresholds used in each study, we could not proceed. Regarding toxicity, NMA using only counts of grade ≥ 3 events was too broad to efficiently compare toxicity between trials. Lastly, OS and possibly ORR data in the Javelin Renal 101 trial were still immature at the time of analysis; thus, the Ave-Axi combination ranking may change with a longer follow-up. Despite a comparable median follow-up, Pembro-Axi exhibited superiority in terms of OS, whereas Ave-Axi surprisingly did not. Our indirect comparison was indeed in favor of Pembro-Axi, but more updates and trials would be needed to further investigate this difference. Therefore, the results of our study should be interpreted cautiously given the underlying hypothesis and potential bias of the estimated effects.Clinicians have concerns about sequencing and identifying predictive biomarkers. More follow-up and reported data from patients in second-line after IO-TKI and IO-IO combination treatments may be of great help to guide decisions about the line of treatment. Our NMA model can grow with each new trial to help decision-making. Other trial results are awaited, comparing pembrolizumab plus lenvatinib vs. everolimus plus lenvatinib vs. sunitinib ; triplet cabozantinib plus nivolumab plus ipilimumab vs. nivolumab plus ipilimumab ; and nivolumab plus cabozantinib vs. cabozantinib plus nivolumab plus ipilimumab vs. sunitinib . Personalized-therapy-driven trials based on molecular profiling such as the BIONIKK trial (NCT02960906) may also provide new insights for clinical decision.Our results support the importance of the IMDC risk score for the comparative efficacy assessment of new combinations in the first-line setting of metastatic clear-cell renal cell carcinoma. This is important given the lack of predictive validated biomarkers. Our results suggest a PFS, ORR, and OS superiority of IO-TKI, compared with IO-IO combinations, regardless of the IMDC risk group. In favorable risk-group patients, PFS and OS were superior with IO-TKI, but these differences vanished in the intermediate/poor risk group. Overall, based on the current evidence, pembrolizumab-axitinib may have a slight advantage over the two other combinations.


Important differences in comorbidities and clinical characteristics exist between women and men with heart failure (HF). In particular, differences in the kinetics of biological circulating biomarkers—a critical component of cardiovascular care—are highly relevant. Most circulating HF biomarkers are assessed daily by clinicians without taking sex into account, despite the multiple gender-related differences observed in plasma concentrations. Even in health, compared to men, women tend to exhibit higher levels of natriuretic peptides and galectin-3 and lower levels of cardiac troponins and the cardiac stress marker, soluble ST2. Many biological factors can provide a reliable explanation for these differences, like body composition, fat distribution, or menopausal status. Notwithstanding, these sex-specific differences in biomarker levels do not reflect different pathobiological mechanisms in HF between women and men, and they do not necessarily imply a need to use different diagnostic cut-off levels in clinical practice. To date, the sex-specific prognostic value of HF biomarkers for risk stratification is an unresolved issue that future research must elucidate. This review outlines current evidence regarding gender-related differences in circulating biomarkers widely used in HF, the pathophysiological mechanisms underlying these differences, and their clinical relevance. Heart failure (HF) is a major health care issue in both sexes; it is associated with significant morbidity, mortality, and health care costs . SeveralIn 2007, the National Academy of Clinical Chemistry and the International Federation of Clinical Chemistry recommended the development of sex-specific reference ranges for cardiac biomarkers used routinely in clinical practice . ConsequImproving HF care requires consideration of all gender-related differences. Moreover, improving our understanding of gender-specific differences in HF biomarkers might enrich our understanding of physiological differences between men and women with HF. Taking these points into consideration, this review covers the four most important and frequent HF biomarkers available in daily clinical practice, with a focus on differences between women and men .Currently, assays are available for detecting cardiac troponin (cTn) with high clinical sensitivity and high specificity for myocardial tissue. Moreover, many assays are capable of early cTn detection, when necrosis is minimal or even in the absence of cell necrosis by different mechanisms . Due to these features, cTn has become the standard biomarker for myocardial damage and the preferred biomarker for diagnosing acute myocardial infarction. In addition, individuals in the HF population frequently have increased concentrations of high-sensitivity cTn (hs-cTn). In up to 93% of patients with acute HF and up to 74% of patients with stable chronic HF, hs-cTn concentrations are above the 99th percentile of the reference value . HoweverMarked variations in cTn concentrations have been detected between women and men, with higher values commonly found in men , 13. ThiIn the HF spectrum, the diagnostic utility of cTn is limited; however, its prognostic value is highly relevant. Studies by Parikh et al.  and by dNatriuretic peptides are a group of neurohormones that play a central role in the regulation of electrolytes and water balance through their diuretic and natriuretic effects . In humain vitro diagnostic tests was published in the early 2000s. Comparative studies that measured concentrations of the active BNP hormone vs. NT-proBNP generally demonstrated diagnostic equivalency for differentiating HF from other causes of shortness of breath. The proBNP molecule contains 108 amino acids. The first 76 amino acids are biologically inactive, and amino acids 77–108 constitute the biologically active component of the molecule, BNP.The most extensive evidence on the value of BNP-related Currently, NT-proBNP is a well-established, powerful biomarker for the diagnosis and prognosis of HF –37. It iAlthough sex-specific differences in NT-proBNP levels have been documented, the precise mechanism that gives rise to higher NT-proBNP levels in women than in men is not well-established in healthy subjects. Several possible explanations have been explored. One reasonable pathobiological explanation involves the effects of sex hormones. Strong clinical evidence has shown that testosterone could lower cardiac natriuretic peptide levels, probably by upregulating neprilysin activity; this effect might explain why NT-proBNP levels are lower in men than in women , 46. OthHowever, these sex-related dissimilarities observed in the general population appeared to be less pronounced in HF and other disease populations associated with upregulated NT-proBNP levels. Some studies have reported the opposite findings, noting that natriuretic peptide levels were similar or lower in women compared to men , 54. HowNT-proBNP levels have shown clinical relevance in predicting the incidence of HF in the general population. High levels were associated with a high risk of HF –61, whicST2 is a member of the interleukin-1 receptor family. ST2 exists in both membrane-bound (ST2L) and soluble (sST2) forms. Interleukin-33 (IL-33) is the functional ligand for ST2L, and in the heart, the IL-33/ST2L interaction mitigates cellular responses to mechanical stress. This function is thought to be mediated by the inhibition of apoptosis and cell death . Loss ofClinical data has suggested that sex has a potentially important effect on sST2 concentrations. Women exhibited lower sST2 levels than age-matched men . In a laDue to the prognostic value of ST2 –75 and iGalectin-3 , a unique member of the chimera-type galectins, is involved in a large number of disease processes. It is widely expressed in human tissues, including epithelial, endothelial, and immune cells . Gal-3 pRecent data from population-based studies –84 have In the Framingham Heart Study, an analysis of more than 3,000 participants showed that elevated Gal-3 concentrations were associated with increases in the risk of new-onset HF . This association was clearly attenuated after adjusting for kidney function . This “rIn the last decade there has been an intensified interest in additional biomarkers as an objective alternative for diagnosis, prognosis or personalized treatment in HF. Among them is the growth differentiation factor-15 (GDF-15), a member of the transforming growth factor-?? cytokine superfamily with anti-apoptotic, anti-hypertrophic, and anti-inflammatory properties. GDF-15 is weakly expressed in tissues under normal conditions. Although its pathobiology is not fully understood, it is strongly induced by macrophages in response to inflammation and tissue injury. It appears to be only moderately expressed in the heart . DespiteMost circulating HF biomarkers are used daily by clinicians without taking sex into account. Nevertheless, multiple gender-related differences have been observed in the plasma concentrations of several biomarkers. In the healthy population, women tend to exhibit higher levels of natriuretic peptides and Gal-3 and lower levels of cTn and sST2, compared to men. Plausible biological explanations for these sex-related differences have been postulated, like differences in body composition, fat distribution, or sex hormones. Nonetheless, several clinical studies have shown that these differences were attenuated in patients with HF, despite the fact that distinct gender distributions have been extensively described for different HF phenotypes. Moreover, these sex-related differences do not necessarily translate into a need to use different cut-off points for men and women, either for HF diagnosis or HF prognosis, in clinical practice. Future research should explore the clinical value of considering possible sex-related differences in specific HF biomarkers, in both diagnostic and prognostic settings, with the aim of improving HF management and patient care.GC drafted the manuscript with support from AB-G. All the authors contributed to manuscript revision and read and approved the submitted version.AB-G has received speaker fees from Roche Diagnostics. AB-G and JL report a relationship with Critical Diagnostics. The remaining 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.


Intraclass correlation coefficients of agreement and coefficients of variation were further calculated. Chi-square tests were used to determine the dietary assessment method with the greatest participant completion rate. At baseline (n = 104), there were no significant differences between the results of the CDHQII and three 24-h recalls (averaged), with overall moderate correlation coefficients. At 3-months (n = 53), there were significant differences (p < 0.05) between dietary intake collection methods for all nutrients assessed in this study, except for saturated fat , unsaturated fat , protein  and sodium (mg). Correlation coefficients were moderate. A significantly greater proportion of participants completed the three 24-h recalls compared to the CDHQII after 3 months . The CDHQII provided estimates of mean nutritional intake  that were comparable to mean intake established from three 24-h recalls, at baseline and was validated in a sample of primarily middle-aged, college-educated, Caucasian female adults with overweight and obesity for mean baseline or cross-sectional measurement only but not for assessing individual/patient dietary intake in clinical practice (r = 0.30–0.68). This tool was not validated at 3-month follow-up. Additionally, participants preferred the three 24-h recalls to the online, past-month CDHQII.Dietary intake tools are used in epidemiological and interventional studies to estimate nutritional intake. The past-month Canadian Diet History Questionnaire II (CDHQII) has not yet been validated. This study aimed to assess the validity of the CDHQII in adults by comparing dietary results from the CDHQII to the same participants’ 24-h recalls consisting of two weekdays and one weekend day. The recalls were collected using the validated multiple-pass method. Participants were asked to complete both tools at baseline, and again at 3-month follow-up. The study further aimed to determine which dietary intake tool was preferred by study participants by comparing completion rates. Data collection occurred at baseline (pre-intervention) and 3-month follow-up (post-intervention). Paired sample  Dietary assessment tools are commonly used by healthcare professionals to assess the nutritional status of their patients, and by researchers in epidemiological and interventional studies to advance knowledge in nutritional science. Generally, short-term intake of food, beverages, and supplements is captured by multiple-day dietary recalls, such as three 24-h recalls . To detePrevious studies have indicated that FFQs administered online is the preferred intake method over paper-versions, and they are comparably reliable for measuring estimated dietary intakes . The onlThe American Diet History Questionnaire, also known as the National Cancer Institute/Block Questionnaire, has been validated in previous studies to accurately estimate dietary intakes in various populations ,10,11,12The original American Diet History Questionnaire was adapted using Canadian nutrient databases to reflect differences in American and Canadian fortification processes to create the CDHQI and CDHQII ,16. Furtpast-month CDHQII to any other dietary intake method, and thus, this more short-term dietary data collection tool has not yet been validated. Assessing the validity of the web-based past-month CDHQII is important in order to enhance nutrition research in Canada by potentially contributing to the number of valid tools available for collection of estimated dietary intake among participants. Based on this knowledge gap, the purpose of this study was to assess the validity of the past-month online CDHQII by comparing the nutritional results to those of three 24-h recalls (averaged) collected using the validated multiple-pass method : energy , total fat, saturated fat, unsaturated fat, protein, carbohydrates, and sodium. The secondary objectives of this study were (a) to assess the validity prior to and following the implementation of an intervention involving training on measuring serving sizes; and (b) to determine participant preference for the past-month, online CDHQII or three 24-h recalls. The dataset from the Nutrigenomics, Overweight/Obesity and Weight Management trial was used to conduct this study. This pragmatic trial was registered with clinicaltrials.gov (NCT03015012) and was approved by the Western University Research Ethics Board (#108511). Inclusion criteria were as follows: English-speaking, enrolled in the Group Lifestyle Balance™ (GLB) weight management program, not seeing another healthcare provider for weight loss advice outside of the study, willing to undergo genetic testing, BMI ≥ 25 kg/mdetailed .N = 140). Participants were primarily college-educated, middle-aged, Caucasian women with obesity (class II). Baseline data were collected during a pre-intervention two-week run-in period, and participants were asked to complete both three 24-h dietary recalls (two weekdays and one weekend day) and the past-month, online CDHQII. All participants who completed baseline dietary intake data collection participated in the trial; none were lost to follow-up during the run-in. As part of the nutrition intervention (after the run-in period), participants were asked to measure and record all of the foods and beverages they consumed for at least one week [In brief, adult participants from Elgin and Middlesex Counties in Ontario were recruited from the GLB lifestyle change weight management program at the East Elgin Family Health Team . Within each category respondents are asked more specific questions about precise products that they consume as well as their quantities and frequencies. The CDHQII uses s method . Previous method . The mulllection .IBM SPSS Statistics, Version 26.0  was used to conduct paired sample t-tests to compare mean values for energy , dietary fat, saturated fat, unsaturated fat, protein, carbohydrates, and sodium from the past-month CDHQII and three 24-h recalls. Chi-square tests were used to compare the proportion of participants completing each dietary intake tool at baseline and 3-month follow-up. Statistically significant values are determined at p < 0.05. Intraclass correlation coefficients of agreement as well as coefficients of variation were additionally calculated. p < 0.02). Additionally, a significantly greater proportion of participants completed both dietary assessment tools at baseline compared to 3-month follow-up (p < 0.01). These indicators of participant preference are further detailed in A total of 140 participants met the predetermined inclusion criteria signed the informed consent form and were enrolled in the study. At baseline, there were no significant differences in the proportion of participants who completed the CDHQII vs. the three 24-h recalls. At 3-month follow-up, there was a significantly greater proportion of participants who completed the three 24-h recalls compared to the CDHQII (p < 0.05) participants completing the CDHQII compared to the three 24-h recalls at 3-month follow-up, it was determined that participants preferred completing the three 24-h recalls. In addition, given that 74% and 41% of participants completed both dietary assessment methods at baseline and 3-month follow-up, respectively, including both tools in a single study appears to lead to substantial participant burden. Therefore, when designing future studies researchers may want to consider selecting only one of these dietary intake tools, basing their decision on individualized study implications and keeping in mind participant preferences for the three 24-h recalls. This is of particular importance for reducing any risk of attrition bias in studies reporting on change in dietary intake over time. Overall, this study found that mean values established from the CDHQII, when used as a baseline dietary assessment tool, were not significantly different from three 24-h recalls and therefore the CDHQII is a valid tool for assessing mean nutritional values for populations as a baseline or cross-sectional measure. However, given that there were weak to moderate correlations, the CDHQII has not been validated for use on an individual level, such as for use with nutritional counseling of patients in a clinical setting. The use of the CDHQII tool for assessing follow-up dietary data (even after the provision of an intervention that included hands-on education about accurate portion sizes) should be cautioned both from an individual patient point of view and for assessing mean intakes of populations. In particular, the CDHQII significantly underestimated calories and grams of macronutrients, however it provided similar follow-up measures  for %kcal of protein, unsaturated and saturated fat, and mg of sodium. Given these findings, the past-month CDHQII may be more accurate for assessing populations’ mean dietary intake levels in observational studies with a single time-point as opposed to observational or interventional studies with multiple time points. The results of this study have important implications for clinical practice and nutrition research. First, with significantly fewer , thus limiting generalizability. Past work by Liu et al., for example, validated a 169-item FFQ developed for adults in Newfoundland and Labrador, which therefore can be justifiably used as a dietary intake assessment method in this particular population, but should be validated for reliable use in other populations . SimilarOverall, the present study demonstrated that the online, past-month CDHQII provides estimates of mean nutritional intake for baseline calories, macronutrients and sodium that are comparable to those determined from validated, three 24-h recalls in a sample of primarily middle-aged, college-educated, adult Caucasian women enrolled in a weight management program. Thus, this tool was validated for baseline or cross-sectional measures for calories, macronutrients and sodium, but should be cautioned for individual estimates given the weak to moderate intraclass correlation coefficients. Therefore, the use of the CDHQII for assessing individual dietary intake  is not recommended. Additionally, the tool was not validated at 3-month follow-up and therefore results from follow-up online, past-month CDHQIIs should be interpreted with caution in this population, especially for calories and grams of macronutrients.


Background: Physical activity closely relates to cognition and brain structure as we age. However, the neural mechanisms underlying this relationship in humans remain less clear. Functional connectivity (FC), measured by task-free functional MRI (tf-fMRI) is a dynamic marker of network activity and may be a sensitive indicator of the brain’s response to exercise over time. We aimed to test the longitudinal relationship between physical activity and FC trajectories in functionally normal older adults.Methods: Two hundred and twelve functionally normal, longitudinally-followed older adults completed the Physical Activity Scale for the Elderly (PASE) and tf-fMRI scans at each visit [mean = 1.5 visits (range:1–3)]. We studied FC of the default mode network (DMN), frontal-parietal (FP), subcortical networks (SubCort), and frontal-subcortical inter-network connectivity (FS), given that previous studies implicate these regions in age-related changes. Linear mixed-effects models examined the relationship between within-person changes in PASE and FC (in SD units), covarying for age, sex, education and systemic cardiovascular risk factors . We additionally examined models covarying for DTI fractional anisotropy (FA) and mean diffusivity (MD) of tracts underlying networks of interest, as a marker of cerebrovascular disease. Furthermore, we examined the longitudinal relationship between PASE and neuropsychological trajectories.Results: In our first model, within-subject increases in physical activity tracked with increasing SubCort  and FS inter-network  synchrony, while between-subject parameters did not reach significance . No significant longitudinal associations were observed between PASE and DMN (β = −0.02 p = 0.89) or FP networks . Adjusting for markers of cerebrovascular health (FA/MD) did not change estimated effects . Associations between changes in physical activity and neuropsychological trajectories were small (β = −0.14 to 0.002) and did not reach statistical significance .Conclusions: Our findings suggest that changes in exercise over time are specifically associated with frontal-subcortical processes in older adults. This relationship appears to be independent of cardio- or cerebrovascular disease, possibly driven by a more direct neural response to exercise. Cognitive decline is a public health issue of global proportions, as rates of dementia are rapidly increasing around the world. Currently, about 50 million people are living with dementia, and this number is projected to increase threefold in the next 30 years , also referred to as “resting-state fMRI,” is a widely-used tool to explore the integrity and function of large-scale brain networks. Functional connectivity (FC) is one factor that has been reported to be affected by the aging process. It is thought to reflect typical cognitive changes in aging , and the subcortical network (SN) are widely-examined networks that are associated with abilities such as introspection, executive function, and motor function, respectively, we focused our preliminary investigations on connectivity within these three networks. We hypothesized that an increase in exercise would relate to increased synchrony within these networks. By providing longitudinal data on the relationship between physical activity and the brain’s FC, we hope to inform how this widely-accessible modifiable lifestyle factor may impact brain health, and how FC could be used to track those changes.In this study, we included 212 older adults who were longitudinally-followed in the Hillblom Healthy Aging Study at the UCSF Memory and Aging Center see . The HilPhysical activity was measured using the Physical Activity Scale for the Elderly (PASE), a validated measure of self-reported activity levels for the geriatric population. This measure was developed in older adults and asks participants to describe their physical activity engagement over 7 days, including questions aimed to assess duration, frequency, exertion level, and amount of physical activity. A composite score was calculated according to the scoring manual  using a mask in the central portion of the lateral ventricles and for the white matter using a mask of the highest probability cortical white matter as labeled in the FSL tissue prior mask. Additional nuisance parameters included the three translational and three rotational motion parameters, the temporal derivatives of the previous eight terms (WM/CSF/6 motion), and the squares of the previous 16 terms , scanned and analyzed using the same pipeline as the subjects in the longitudinal portion of this study. The details of our process have been described elsewhere ], resting heart rate, and resting blood pressure.subcortical network: anterior limb of the internal capsule and the posterior thalamic radiation; executive-subcortical network: anterior limb of the internal capsule, posterior thalamic radiations, superior longitudinal fasciculus, genu, body, and splenium of the corpus callosum. The Brainnetome regions comprising the tf-fMRI networks  were then applied to the T1 scans to extract gray matter volumes. The regional volumes for all regions comprising a given network were summed to obtain the network’s gray matter volume.To determine the relative independence of the relationship between physical activity and fMRI connectivity from white matter changes  or gray matter atrophy in the queried networks, we then extracted fractional anisotropy (FA), mean diffusivity (MD), and gray matter volume from the specific networks of interest. Based on known anatomical relationships, DTI-based white matter tracts were extracted for: First, we fitted baseline cross-sectional multivariable linear regression models examining the relationship between PASE scores and FC in our networks of interest, covarying for demographic factors . Parallel models examined the relationship between PASE scores and neuropsychological test performances, again adjusting for age, sex, and years of education. Our primary analyses focused on our three networks of interest . Then, in the networks that reached statistical significance, we conducted secondary analyses to examine their inter-network relationships, to better understand the associations at play.Next, we conducted linear mixed-effects models to examine the longitudinal relationship between changes in PASE scores and FC trajectories in the networks of interest, as well as between PASE scores and cognitive performance. In all models, following  were selected for follow-up analyses, to explore whether this relationship upheld after adjusting for markers of cerebrovascular integrity. For this purpose, we conducted parallel models covarying for gray matter volume and FA, or gray matter volume and MD in the gray matter ROIs and white matter tracts associated with the given network of interest. We re-scaled predictors to standard deviation units, in concordance with standardized beta coefficients, as seen in In our first longitudinal model, we examined how between- and within-subject changes in PASE scores related to changes in FC, adjusting for demographic factors , as well as markers of cardiovascular health  as covariates. Models in which networks significantly tracked with changes in PASE scores , intra-executive network connectivity , intra-subcortical network connectivity , and executive-subcortical inter-network connectivity . Similarly, the cross-sectional relationship between physical activity and cognitive performance was small and nonsignificant .At baseline, reported physical activity levels demonstrated weak negative relationships with FC in brain regions of interest: intra-DMN network connectivity  and frontal-subcortical inter-network  synchrony over time on fMRI. Neither within-person nor between-person changes in PASE scores were significantly related to DMN  or intra-frontoparietal network  connectivity , while between-subject effects continued to be small and did not reach statistical significance . Similarly, within-subject increases in PASE scores tracked with greater inter-executive-subcortical network synchrony (β = 0.28 p = 0.03), yet between-subject effects were small and did not reach statistical significance . Moreover, we examined parallel models adjusting for MD and gray matter and observed the same pattern as when controlling for FA .Both within- and between-subject self-reported levels of physical activity demonstrated small, nonsignificant associations with cognitive performance  levels . SW and AW worked on neuroimaging processing and database cleaning. JK and KC supervised the project and provided critical edits of the 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.


However, the underlying molecular mechanisms for these differences are still not fully understood. In this study, we used a robust rank aggregation (RRA) method to discover robust differentially expressed genes (DEGs) between fetal bone marrow mesenchymal stem cells (fMSCs) and aged adult bone marrow mesenchymal stem cells (aMSCs). Multiple methods, including gene set enrichment analysis (GSEA), Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed for functional annotation of the robust DEGs, and the results were visualized using the R software. The hub genes and other genes with which they interacted directly were detected by protein–protein interaction (PPI) network analysis. Correlation of gene expression was measured by Pearson correlation coefficient. A total of 388 up-regulated and 289 down-regulated DEGs were identified between aMSCs and fMSCs. We found that the down-regulated genes were mainly involved in the cell cycle, telomerase activity, and stem cell proliferation. The up-regulated DEGs were associated with cell adhesion molecules, extracellular matrix (ECM)–receptor interactions, and the immune response. We screened out four hub genes, MYC, KIF20A, HLA-DRA, and HLA-DPA1, through PPI-network analysis. The MYC gene was negatively correlated with TXNIP, an age-related gene, and KIF20A was extensively involved in the cell cycle. The results suggested that MSCs derived from the bone marrow of an elderly donor present a pro-inflammatory phenotype compared with that of fMSCs, and the HLA-DRA and HLA-DPA1 genes are related to the immune response. These findings provide new insights into the differences between aMSCs and fMSCs and may suggest novel strategies for ex vivo expansion and application of adult MSCs.Stem cells from fetal tissue protect against aging and possess greater proliferative capacity than their adult counterparts. These cells can more readily expand  This me1. The screening criteria of datasets were inclusion of gene expression data of BM-MSCs from fetal and aged donors. Eventually, two datasets, GSE97311  from RRA analysis.The microarray data of GSE97311 and GSE68374 were initially normalized and differential expression was analyzed using the R software though the “limma” package . The res2 : H.all.v7.symbles.gmt, c2.cp.kegg.v7.1.symbols.gmt, and other interesting gene sets involved in the oxidative response, production of interleukin 6, telomerase activity, and stem cell self-renewal in c5.bp.v7.1.symbols.gmt. The GseaPreranked tool was then used to perform enrichment analysis for all the DEGs integrated via RRA method, which are ranked by log FC from large to small. Gene set permutations were performed 1000 times for each analysis. We then visualized the results of GSEA using “ggplot2” in the R package , followed by FMO3 , and TMEM140 . Moreover, FBN ; SCD ; CLDN1  were the most significant down-regulated genes.The expression profiles of aged adult BM-MSCs (aMSCs) were compared with those of fetal BM-MSCs (fMSCs). Based on the screening criteria of ed genes . In addied genes . We inteed genes , which fThe ranked list of DEGs is shown in To further determine the functions of robust DEGs in specific biological processes, we performed GSEA analysis related to aging and stem cell self-renewal. The GO annotation in terms of response to oxidative stress and IL-6 production enriched in the aMSC group . The GO Staphylococcus aureus infection, hematopoietic cell lineage, and extracellular matrix (ECM)–receptor interaction. Unlike the other pathways, the peroxisome proliferator-activated receptor (PPAR) signaling pathway was more likely to be inhibited in aMSCs  contained 144 nodes and 291 edges. We screened four hub genes, considering the degree (DC) and betweenness (BC) centrality  and KIF20A  were up-regulated in the fMSC group, and HLA-DRA  and HLA-DPA1  were up-regulated in the aMSC group. We then selected their first neighbors and structured the respective sub-networks. As shown in MYC; and 18 nodes and 89 edges in the sub-network of KIF20A. Both HLA-DRA and HLA-DPA1 were part of the same network, which included 12 nodes and 34 edges.The PPI network established by the most robust DEGs  are promising sources for tissue engineering and regenerative medicine. Human fetal MSCs (hf-MSCs) have more primitive expression profiles and greater proliferative capacity than their adult counterparts . These creported . The undIn this study, we used bioinformatics to mine the underlying molecular mechanisms that explain the difference between aMSCs and fMSCs. To our best knowledge, this is the first study to use the RRA method to analyze the difference between aMSC and fMSC sources in human bone marrow. AKR1C3. This gene may play an important role in the pathogenesis of allergic diseases such asthma and may have a role in controlling cell growth or differentiation. The most significantly up-regulated gene in fMSCs was FBN2, which regulates the early processes of elastic fiber assembly and osteoblast maturation.Only two datasets in the GEO database, GSE97311 and GSE 68374, met our experimental requirements. We performed robust differential expression profiling analysis using the two existing GEO datasets and obtained 677 robust DEGs, including 388 up-regulated and 289 down-regulated DEGs in aMSCs compared with fMSCs. The most significantly up-regulated gene in aMSCs was MYC targets, were all related to proliferation. These results further support the notion that fMSCs have greater self-renewal abilities than aMSCs and are consistent with earlier observations . TXNIP plays a crucial role in aging processes. Age-related up-regulation of TXNIP results in reduced resistance to oxidative stress, and thereby accelerates aging. The present study reveals that fMSCs with high expression of MYC and low expression TXNIP may explain why fMSCs possess greater proliferative capacity and are more resistant to aging. The negative correlation between MYC and TXNIP in BM-MSCs warrants further research. Nevertheless, we must also acknowledge that high levels of c-MYC increase the risk of oncogenesis  with MYC.The mitotic kinesin, gulation . It is sgulation . A recend by MYC . There iHLA-DRA and HLA-DPA1 belong to the major histocompatibility complex class II, are up-regulated in aMSCs, and mainly involved in antigen procession and presentation. The aMSCs express intermediate levels of HLA class I and low levels of HLA class II, while fMSCs express no HLA class II  . The telMYC, KIF20A, HLA-DRA, and HLA-DPA1. Expression of the MYC gene was negatively correlated with that of TXNIP, a known senescence-associated gene. Furthermore, KIF20A is extensively linked with the cell cycle. The other two core genes, HLA-DRA and HLA-DPA1, are implicated in the immune response and may be induced by age-related inflammatory conditions. We infer that BM-MSCs derived from elderly donors may have age-related drawbacks. These cells show lower proliferative capacity and a pro-inflammatory phenotype. More experiments are required for further verification of these findings.Through data mining and network analysis, we detected four hub genes, The original contributions presented in the study are included in the article/XYL conceived and designed the research, performed analysis, and wrote the majority of the manuscript. BZ, YL, HJ, and ZL supervised the research. MY, XPL, JD, KZ, XZ, LL, and JW contributed to data collation. 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.